UnemploymentandPatents.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a3995de4",
   "metadata": {},
   "source": [
    "# In this notebook, we will be analyzing if there is a trend towards a lower or higher percentage of unemployment when there are being more patents being made throughout the years. If there are any dips, will we see any dips that happen in the other dataset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ee5b3743",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Here, we are going to load the generic g_patent and g_cpc_current DataFrames as well as our pandas, matplotlib etc\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set( style = 'white' )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2cbb6d2b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here is a variable change in the width of the string for the columns. I am placing it here as it may need\n",
    "# to be changed often, so I will move it right here!\n",
    "pd.options.display.max_colwidth = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a2eb3d8d",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>patent_id</th>\n",
       "      <th>patent_type</th>\n",
       "      <th>patent_date</th>\n",
       "      <th>patent_title</th>\n",
       "      <th>patent_abstract</th>\n",
       "      <th>wipo_kind</th>\n",
       "      <th>num_claims</th>\n",
       "      <th>withdrawn</th>\n",
       "      <th>filename</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000000</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Coherent LADAR using intra-pixel quadrature detection</td>\n",
       "      <td>A frequency modulated (coherent) laser detection and ranging system includes a read-out integrated circuit formed with a two-dimensional array of detector elements each including a photosensitive region receiving both return light reflected from a target and light from a local oscillator, and local processing circuitry sampling the output of the photosensitive region four times during each sample period clock cycle to obtain quadrature components. A data bus coupled to one or more outputs of each of the detector elements receives the quadrature components from each of the detector elements for each sample period and serializes the received quadrature components. A processor coupled to the data bus receives the serialized quadrature components and determines an amplitude and a phase for at least one interfering frequency corresponding to interference between the return light and the local oscillator light using the quadrature components.</td>\n",
       "      <td>B2</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10000001</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Injection molding machine and mold thickness control method</td>\n",
       "      <td>The injection molding machine includes a fixed platen, a moveable platen moving forward and backward by a toggle link, a base plate supporting the toggle link, a driving part for mold clamping to operate the toggle link, a driving part for mold thickness adjustment to adjust a mold thickness, and a control unit to calculate a movement distance gap before a clamping process by controlling the driving part for mold thickness adjustment to move the base plate backward and then move the base plate forward to a target movement position based on a fold amount of the toggle link, and control the driving part for mold thickness adjustment using a value obtained by deducting the movement distance gap from the fold amount of the toggle link when producing a clamp force.</td>\n",
       "      <td>B2</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10000002</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method for manufacturing polymer film and co-extruded film</td>\n",
       "      <td>The present invention relates to: a method for manufacturing a polymer film, the method including a base film forming step for co-extruding a first resin containing a polyamide-based resin and a second resin containing a copolymer including polyamide-based segments and polyether-based segments; a co-extruded film including a base film including a first resin layer containing a polyamide-based resin, and a second resin layer containing a copolymer having polyamide-based segments and polyether-based segments; to a co-extruded film including a base film including a first resin layer and a second resin layer, which have different melting points; and to a method for manufacturing a polymer film, the method including a base film forming step including a step of co-extruding a first resin and a second resin, which have different melting points.</td>\n",
       "      <td>B2</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10000003</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method for producing a container from a thermoplastic</td>\n",
       "      <td>The invention relates to a method for producing a container (2) from a thermoplastic, having at least one surround (4), provided in the container wall (1), for a container opening. The surround (4) comprises a structure behind which parts of the container wall (1) extend and/or which is penetrated by said parts. The method is carried out using a multi-part blow mold that has at least two mold parts, each having at least one cavity, wherein the surround is placed as an insert in the cavity (10) of the blow mold (7). The method comprises pressing the preform that has been forced into the cavity (10) into the structure of the surround (4) by means of a tool which is brought to bear on the preform (12) on the side of the preform facing away from the cavity (10).</td>\n",
       "      <td>B2</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10000004</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Process of obtaining a double-oriented film, co-extruded, and of low thickness made by a three bubble process that at the time of being thermoformed provides a uniform thickness in the produced tray</td>\n",
       "      <td>The present invention relates to provides a double-oriented film, co-extrude, and of low thickness, with a layered composition that gives the property of being of high barrier to gases and manufactured by the process of co-extrusion of 3 bubbles, which gives the property of when being thermoformed, ensure the distribution of uniform thickness in the walls, base, folds, and corners of the formed tray saving a minimum of 50% of plastic without diminishing its gas barrier and its resistance to puncture.</td>\n",
       "      <td>B2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10000005</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Article vacuum formation method and vacuum forming apparatus</td>\n",
       "      <td>A vacuum forming apparatus is provided that forms an article having a covering bonded to the surface of a substrate in a molding space using a first mold and a second mold. The vacuum forming apparatus is provided with clamps for grasping the covering between the first and second molds arranged at the open positions. The clamps are movable between an interfering position, at which the clamps are located in the movement ranges of the first and second molds, and standby positions, at which the clamps are outside the movement ranges. After the covering is heated, the clamps grasping the covering move to the standby positions and stretch the covering. The first and second molds move to the closed positions and the article is molded between the first and second molds so that the stretched covering and the substrate are bonded to each other.</td>\n",
       "      <td>B2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10000006</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Thermoforming mold device and a process for its manufacture and use</td>\n",
       "      <td>A thermoforming mold device (1) providing a piece with a thin wall starting with a sheet of thermoplastic material is provided. At least one (3) of two parts of the mold (3, 3′) comprises at least one means (4) of local deformation of a sheet (2′) in the mold (3, 3′) in its closed state, the at least one means (4) comprises a piece of hollow molding with a peripheral edge, which can be connected selectively to a source of suction and can be displaced between a folded position, in which the molding piece is situated in close proximity with the wall of the thermoformed piece, and a deployed position, in which the molding piece is applied under pressure with its peripheral edge against the wall of the thermoformed piece upholding the other part of the mold.</td>\n",
       "      <td>B2</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10000007</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>PEX expanding tool</td>\n",
       "      <td>An expanding tool comprising: an actuator comprising a cylindrical housing that defines an actuator housing cavity; a primary ram disposed within the actuator housing cavity, the primary ram defining an internal primary ram cavity; a secondary ram disposed within the internal primary ram cavity; a cam roller carrier coupled to a distal end of the secondary ram; a drive collar positioned within a distal end of the actuator housing cavity; a roller clutch disposed within an internal cavity defined by an inner surface of the drive collar; a shuttle cam positioned between the roller clutch and a distal end of the primary ram; an expander cone coupled to the primary ram; and an expander head operably coupled to the drive collar.</td>\n",
       "      <td>B2</td>\n",
       "      <td>24</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10000008</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Bracelet mold and method of use</td>\n",
       "      <td>A decorated strip of coated, heat-shrinkable, plastic sheet material is placed in a spiral slot formed in a silicone rubber mold. The spiral slot is defined by a spiral wall having a uniform wall thickness. Upon heating in an oven, the material shrinks, forming a resiliently expansible arc-shaped band that can be worn as a bracelet or wristband.</td>\n",
       "      <td>B2</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10000009</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Sterile environment for additive manufacturing</td>\n",
       "      <td>In sterile, additive manufacturing wherein one lamella is successively built upon an underlying lamella until an object is completed, a sterile manufacturing environment is provided. A major chamber large enough to accommodate the manufactured object has sterile accordion pleated sidewalls and a sterile top closed with flap valves. A minor chamber for supporting the nozzles positioned above the major chamber has similar valves in corresponding positions. Nozzles for material deposition penetrate the pair of valves to block air and particles from entry into the major chamber where the nozzles make layer by layer deposition of the object using XY areawise nozzle motion relative to the object as well as Z nozzle vertical motion with the major chamber expanding as the object is formed.</td>\n",
       "      <td>B2</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10000010</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>3-D electrostatic printer using rack and pinion registration system</td>\n",
       "      <td>3-D printing system include development stations positioned to electrostatically transfer build and support materials to an intermediate transfer surface, a transfer station adjacent the intermediate transfer surface, guides adjacent the transfer station, and platens moving on the guides. The guides are shaped to direct the platens to repeatedly pass the transfer station and come in contact with the intermediate transfer surface at the transfer station. The intermediate transfer surface transfers a layer of the build and support materials to the platens each time the platens contact the intermediate transfer surface at the transfer station to successively form layers of the build and support materials on the platens. The platens and the intermediate transfer surface include rack and pinion structures that temporarily join at the transfer station, as the platens pass the transfer station, to align the platens with the intermediate transfer surface as the platens contact the intermed...</td>\n",
       "      <td>B2</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10000011</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Supports for sintering additively manufactured parts</td>\n",
       "      <td>To reduce distortion in an additively manufactured part, a shrinking platform is formed from a metal particulate filler in a debindable matrix. Shrinking supports of the same material are formed above the shrinking platform, and a desired part of the same material is formed upon them. A sliding release layer is provided below the shrinking platform of equal or larger surface area than a bottom of the shrinking platform to lateral resistance between the shrinking platform and an underlying surface. The matrix is debound sufficient to form a shape-retaining brown part assembly including the shrinking platform, shrinking supports, and the desired part. The shape-retaining brown part assembly is heated to shrink all of the components together at a same rate via atomic diffusion.</td>\n",
       "      <td>B1</td>\n",
       "      <td>30</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10000014</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method for producing thermoplastic foam panels by means of at least two heating elements offset in parallel with each other</td>\n",
       "      <td>The present invention relates to a process for the production of at least two-layer thermoplastic foam sheets via thermal welding of at least two thinner thermoplastic foam sheets. In the process of the invention, at least two heating elements are conducted on mutually offset planes between the surfaces to be welded of the thinner thermoplastic foam sheets, and the foam sheets here do not touch the heating elements. The number of layers of the thermoplastic foam sheet is per se a result of the number of thinner thermoplastic foam sheets that are thermally welded to one another. If by way of example three thinner thermoplastic foam sheets are thermally welded to one another, a three-layer thermoplastic foam sheet is per se obtained, and if there are four thinner thermoplastic foam sheets the result is accordingly per se a four-layer thermoplastic foam sheet.</td>\n",
       "      <td>B2</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10000015</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Methods for making optical components, optical components, and products including same</td>\n",
       "      <td>A hermetically sealed optical component includes an optical material including an optical material comprising quantum dots sealed between glass substrates by a hermetic seal including a liquid crystalline polymer.</td>\n",
       "      <td>B2</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10000016</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Film edge sealing device</td>\n",
       "      <td>A film edge sealing device is disclosed herein which has a groove defining a base. The base of the groove of the edge sealing device is oriented at a skewed angle with respect to a longitudinal direction of the conveyor of the heat sealing machine. Edges of a thermoplastic sheet or two stacked layers of thermoplastic sheets are introduced into the groove of the edge sealing device and placed in contact therewith to both heat and melt the edges of the thermoplastic sheet(s) to form a bead and join the edges thereof to form an edge bead seal.</td>\n",
       "      <td>B2</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10000017</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method for mounting a vortex generator and mounting apparatus for carrying out the method</td>\n",
       "      <td>The invention relates to a method for securing an attachment (3, 33) to a component, in particular a rotor blade (1), in which the component is provided with an adhesion surface (36), the attachment (3, 33) is provided with a corresponding adhesion surface (9), the attachment (3, 33) is provided with an adhesive-conveying connection to the corresponding adhesion surface (9), the adhesion surface (36) is placed on the corresponding adhesion surface (9), a gap (53) is formed between the adhesion surface (36) and the corresponding adhesion surface (9), the attachment (3, 33) is pressed against the corresponding adhesion surface (9) and at the same time the adhesive (80) is injected into the gap (53) through the adhesive-conveying connection.</td>\n",
       "      <td>B2</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10000018</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Pull tab design for stretch release adhesive</td>\n",
       "      <td>A stretch release adhesive is disclosed. The stretch release adhesive can be used for extracting an electrical component from an interior surface of a housing of a mobile computing device. The stretch release adhesive can have a double-sided adhesive body configured to adhere the component to the interior surface of the housing. A portion of the double-sided adhesive body is configured to extend out from between the electrical component and the interior surface of the housing to provide a graspable portion. When the stretch release adhesive is adhered between the electrical component and the internal surface of the housing, the stretch release adhesive can receive a pulling force at the graspable portion. If pulled with enough force, the stretch release adhesive will extend outwardly from between the electrical component and the internal surface of the mobile computing device, then completely release the electrical component from the mobile computing device.</td>\n",
       "      <td>B2</td>\n",
       "      <td>13</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10000019</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Installation assembly and associated method for forming a bonded joint</td>\n",
       "      <td>An installation assembly and an associated method for forming a bonded join are provided to permit the adhesive attachment of a first workpiece, such as a patch, to a portion of a second workpiece. The installation assembly and the associated method provide for at least partial debulking of the adhesive prior to curing of the adhesive such that the resulting bondline may have improved mechanical properties as a result of having fewer voids and/or porosity. The installation assembly may include an installation stand and a carrier plate supported by the installation stand and including an attachment surface configured to carry the first workpiece. The installation stand also includes an adjustment mechanism for positioning a carrier plate to a first predefined position to define a gap between the first and second workpieces and also to a second predefined position such that a predetermined bondline thickness is defined between the first and second workpieces.</td>\n",
       "      <td>B2</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10000020</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method and device for producing areas in a printed object having different coefficients of friction</td>\n",
       "      <td>A three-dimensional object printer enables forming portions of an object with a material having a higher melting temperature and a lower coefficient of friction. The printer includes a member, a printhead, and an applicator. A controller operates the printhead to eject a first material having a first coefficient of friction toward the member and operates the applicator to eject a second material having a second coefficient of friction toward the member. The second material has a higher melting temperature and a lower coefficient of friction than the first material. The printer further includes a curing device. The controller operates the curing device to direct radiation toward the member to cure the first material. The second material is cured into the first material.</td>\n",
       "      <td>B2</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10000021</td>\n",
       "      <td>utility</td>\n",
       "      <td>2018-06-19</td>\n",
       "      <td>Method for manufacturing three-dimensional shaped object and three-dimensional shaped object obtained by the same</td>\n",
       "      <td>There is provided a method for manufacturing a three-dimensional shaped object. The method of the present invention comprises the repeated steps of: (i) forming a solidified layer by irradiating a predetermined portion of a powder layer with a light beam, thereby allowing a sintering of the powder in the predetermined portion or a melting and subsequent solidification thereof; and (ii) forming another solidified layer by newly forming a powder layer on the resulting solidified layer, followed by the irradiation of a predetermined portion of the powder layer with the light beam; wherein only the surface portion of the solidified layer, to which a force is applied when the three-dimensional shaped object is used, is subjected to a machining process.</td>\n",
       "      <td>B2</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>ipg180619.xml</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   patent_id patent_type patent_date  \\\n",
       "0   10000000     utility  2018-06-19   \n",
       "1   10000001     utility  2018-06-19   \n",
       "2   10000002     utility  2018-06-19   \n",
       "3   10000003     utility  2018-06-19   \n",
       "4   10000004     utility  2018-06-19   \n",
       "5   10000005     utility  2018-06-19   \n",
       "6   10000006     utility  2018-06-19   \n",
       "7   10000007     utility  2018-06-19   \n",
       "8   10000008     utility  2018-06-19   \n",
       "9   10000009     utility  2018-06-19   \n",
       "10  10000010     utility  2018-06-19   \n",
       "11  10000011     utility  2018-06-19   \n",
       "12  10000014     utility  2018-06-19   \n",
       "13  10000015     utility  2018-06-19   \n",
       "14  10000016     utility  2018-06-19   \n",
       "15  10000017     utility  2018-06-19   \n",
       "16  10000018     utility  2018-06-19   \n",
       "17  10000019     utility  2018-06-19   \n",
       "18  10000020     utility  2018-06-19   \n",
       "19  10000021     utility  2018-06-19   \n",
       "\n",
       "                                                                                                                                                                                              patent_title  \\\n",
       "0                                                                                                                                                    Coherent LADAR using intra-pixel quadrature detection   \n",
       "1                                                                                                                                              Injection molding machine and mold thickness control method   \n",
       "2                                                                                                                                               Method for manufacturing polymer film and co-extruded film   \n",
       "3                                                                                                                                                    Method for producing a container from a thermoplastic   \n",
       "4   Process of obtaining a double-oriented film, co-extruded, and of low thickness made by a three bubble process that at the time of being thermoformed provides a uniform thickness in the produced tray   \n",
       "5                                                                                                                                             Article vacuum formation method and vacuum forming apparatus   \n",
       "6                                                                                                                                      Thermoforming mold device and a process for its manufacture and use   \n",
       "7                                                                                                                                                                                       PEX expanding tool   \n",
       "8                                                                                                                                                                          Bracelet mold and method of use   \n",
       "9                                                                                                                                                           Sterile environment for additive manufacturing   \n",
       "10                                                                                                                                     3-D electrostatic printer using rack and pinion registration system   \n",
       "11                                                                                                                                                    Supports for sintering additively manufactured parts   \n",
       "12                                                                             Method for producing thermoplastic foam panels by means of at least two heating elements offset in parallel with each other   \n",
       "13                                                                                                                  Methods for making optical components, optical components, and products including same   \n",
       "14                                                                                                                                                                                Film edge sealing device   \n",
       "15                                                                                                               Method for mounting a vortex generator and mounting apparatus for carrying out the method   \n",
       "16                                                                                                                                                            Pull tab design for stretch release adhesive   \n",
       "17                                                                                                                                  Installation assembly and associated method for forming a bonded joint   \n",
       "18                                                                                                     Method and device for producing areas in a printed object having different coefficients of friction   \n",
       "19                                                                                       Method for manufacturing three-dimensional shaped object and three-dimensional shaped object obtained by the same   \n",
       "\n",
       "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            patent_abstract  \\\n",
       "0                                                    A frequency modulated (coherent) laser detection and ranging system includes a read-out integrated circuit formed with a two-dimensional array of detector elements each including a photosensitive region receiving both return light reflected from a target and light from a local oscillator, and local processing circuitry sampling the output of the photosensitive region four times during each sample period clock cycle to obtain quadrature components. A data bus coupled to one or more outputs of each of the detector elements receives the quadrature components from each of the detector elements for each sample period and serializes the received quadrature components. A processor coupled to the data bus receives the serialized quadrature components and determines an amplitude and a phase for at least one interfering frequency corresponding to interference between the return light and the local oscillator light using the quadrature components.   \n",
       "1                                                                                                                                                                                                                                        The injection molding machine includes a fixed platen, a moveable platen moving forward and backward by a toggle link, a base plate supporting the toggle link, a driving part for mold clamping to operate the toggle link, a driving part for mold thickness adjustment to adjust a mold thickness, and a control unit to calculate a movement distance gap before a clamping process by controlling the driving part for mold thickness adjustment to move the base plate backward and then move the base plate forward to a target movement position based on a fold amount of the toggle link, and control the driving part for mold thickness adjustment using a value obtained by deducting the movement distance gap from the fold amount of the toggle link when producing a clamp force.   \n",
       "2                                                                                                                                                         The present invention relates to: a method for manufacturing a polymer film, the method including a base film forming step for co-extruding a first resin containing a polyamide-based resin and a second resin containing a copolymer including polyamide-based segments and polyether-based segments; a co-extruded film including a base film including a first resin layer containing a polyamide-based resin, and a second resin layer containing a copolymer having polyamide-based segments and polyether-based segments; to a co-extruded film including a base film including a first resin layer and a second resin layer, which have different melting points; and to a method for manufacturing a polymer film, the method including a base film forming step including a step of co-extruding a first resin and a second resin, which have different melting points.   \n",
       "3                                                                                                                                                                                                                                          The invention relates to a method for producing a container (2) from a thermoplastic, having at least one surround (4), provided in the container wall (1), for a container opening. The surround (4) comprises a structure behind which parts of the container wall (1) extend and/or which is penetrated by said parts. The method is carried out using a multi-part blow mold that has at least two mold parts, each having at least one cavity, wherein the surround is placed as an insert in the cavity (10) of the blow mold (7). The method comprises pressing the preform that has been forced into the cavity (10) into the structure of the surround (4) by means of a tool which is brought to bear on the preform (12) on the side of the preform facing away from the cavity (10).   \n",
       "4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 The present invention relates to provides a double-oriented film, co-extrude, and of low thickness, with a layered composition that gives the property of being of high barrier to gases and manufactured by the process of co-extrusion of 3 bubbles, which gives the property of when being thermoformed, ensure the distribution of uniform thickness in the walls, base, folds, and corners of the formed tray saving a minimum of 50% of plastic without diminishing its gas barrier and its resistance to puncture.   \n",
       "5                                                                                                                                                           A vacuum forming apparatus is provided that forms an article having a covering bonded to the surface of a substrate in a molding space using a first mold and a second mold. The vacuum forming apparatus is provided with clamps for grasping the covering between the first and second molds arranged at the open positions. The clamps are movable between an interfering position, at which the clamps are located in the movement ranges of the first and second molds, and standby positions, at which the clamps are outside the movement ranges. After the covering is heated, the clamps grasping the covering move to the standby positions and stretch the covering. The first and second molds move to the closed positions and the article is molded between the first and second molds so that the stretched covering and the substrate are bonded to each other.   \n",
       "6                                                                                                                                                                                                                                              A thermoforming mold device (1) providing a piece with a thin wall starting with a sheet of thermoplastic material is provided. At least one (3) of two parts of the mold (3, 3′) comprises at least one means (4) of local deformation of a sheet (2′) in the mold (3, 3′) in its closed state, the at least one means (4) comprises a piece of hollow molding with a peripheral edge, which can be connected selectively to a source of suction and can be displaced between a folded position, in which the molding piece is situated in close proximity with the wall of the thermoformed piece, and a deployed position, in which the molding piece is applied under pressure with its peripheral edge against the wall of the thermoformed piece upholding the other part of the mold.   \n",
       "7                                                                                                                                                                                                                                                                             An expanding tool comprising: an actuator comprising a cylindrical housing that defines an actuator housing cavity; a primary ram disposed within the actuator housing cavity, the primary ram defining an internal primary ram cavity; a secondary ram disposed within the internal primary ram cavity; a cam roller carrier coupled to a distal end of the secondary ram; a drive collar positioned within a distal end of the actuator housing cavity; a roller clutch disposed within an internal cavity defined by an inner surface of the drive collar; a shuttle cam positioned between the roller clutch and a distal end of the primary ram; an expander cone coupled to the primary ram; and an expander head operably coupled to the drive collar.   \n",
       "8                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               A decorated strip of coated, heat-shrinkable, plastic sheet material is placed in a spiral slot formed in a silicone rubber mold. The spiral slot is defined by a spiral wall having a uniform wall thickness. Upon heating in an oven, the material shrinks, forming a resiliently expansible arc-shaped band that can be worn as a bracelet or wristband.   \n",
       "9                                                                                                                                                                                                                  In sterile, additive manufacturing wherein one lamella is successively built upon an underlying lamella until an object is completed, a sterile manufacturing environment is provided. A major chamber large enough to accommodate the manufactured object has sterile accordion pleated sidewalls and a sterile top closed with flap valves. A minor chamber for supporting the nozzles positioned above the major chamber has similar valves in corresponding positions. Nozzles for material deposition penetrate the pair of valves to block air and particles from entry into the major chamber where the nozzles make layer by layer deposition of the object using XY areawise nozzle motion relative to the object as well as Z nozzle vertical motion with the major chamber expanding as the object is formed.   \n",
       "10  3-D printing system include development stations positioned to electrostatically transfer build and support materials to an intermediate transfer surface, a transfer station adjacent the intermediate transfer surface, guides adjacent the transfer station, and platens moving on the guides. The guides are shaped to direct the platens to repeatedly pass the transfer station and come in contact with the intermediate transfer surface at the transfer station. The intermediate transfer surface transfers a layer of the build and support materials to the platens each time the platens contact the intermediate transfer surface at the transfer station to successively form layers of the build and support materials on the platens. The platens and the intermediate transfer surface include rack and pinion structures that temporarily join at the transfer station, as the platens pass the transfer station, to align the platens with the intermediate transfer surface as the platens contact the intermed...   \n",
       "11                                                                                                                                                                                                                        To reduce distortion in an additively manufactured part, a shrinking platform is formed from a metal particulate filler in a debindable matrix. Shrinking supports of the same material are formed above the shrinking platform, and a desired part of the same material is formed upon them. A sliding release layer is provided below the shrinking platform of equal or larger surface area than a bottom of the shrinking platform to lateral resistance between the shrinking platform and an underlying surface. The matrix is debound sufficient to form a shape-retaining brown part assembly including the shrinking platform, shrinking supports, and the desired part. The shape-retaining brown part assembly is heated to shrink all of the components together at a same rate via atomic diffusion.   \n",
       "12                                                                                                                                    The present invention relates to a process for the production of at least two-layer thermoplastic foam sheets via thermal welding of at least two thinner thermoplastic foam sheets. In the process of the invention, at least two heating elements are conducted on mutually offset planes between the surfaces to be welded of the thinner thermoplastic foam sheets, and the foam sheets here do not touch the heating elements. The number of layers of the thermoplastic foam sheet is per se a result of the number of thinner thermoplastic foam sheets that are thermally welded to one another. If by way of example three thinner thermoplastic foam sheets are thermally welded to one another, a three-layer thermoplastic foam sheet is per se obtained, and if there are four thinner thermoplastic foam sheets the result is accordingly per se a four-layer thermoplastic foam sheet.   \n",
       "13                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    A hermetically sealed optical component includes an optical material including an optical material comprising quantum dots sealed between glass substrates by a hermetic seal including a liquid crystalline polymer.   \n",
       "14                                                                                                                                                                                                                                                                                                                                                                                                                                                                       A film edge sealing device is disclosed herein which has a groove defining a base. The base of the groove of the edge sealing device is oriented at a skewed angle with respect to a longitudinal direction of the conveyor of the heat sealing machine. Edges of a thermoplastic sheet or two stacked layers of thermoplastic sheets are introduced into the groove of the edge sealing device and placed in contact therewith to both heat and melt the edges of the thermoplastic sheet(s) to form a bead and join the edges thereof to form an edge bead seal.   \n",
       "15                                                                                                                                                                                                                                                             The invention relates to a method for securing an attachment (3, 33) to a component, in particular a rotor blade (1), in which the component is provided with an adhesion surface (36), the attachment (3, 33) is provided with a corresponding adhesion surface (9), the attachment (3, 33) is provided with an adhesive-conveying connection to the corresponding adhesion surface (9), the adhesion surface (36) is placed on the corresponding adhesion surface (9), a gap (53) is formed between the adhesion surface (36) and the corresponding adhesion surface (9), the attachment (3, 33) is pressed against the corresponding adhesion surface (9) and at the same time the adhesive (80) is injected into the gap (53) through the adhesive-conveying connection.   \n",
       "16                             A stretch release adhesive is disclosed. The stretch release adhesive can be used for extracting an electrical component from an interior surface of a housing of a mobile computing device. The stretch release adhesive can have a double-sided adhesive body configured to adhere the component to the interior surface of the housing. A portion of the double-sided adhesive body is configured to extend out from between the electrical component and the interior surface of the housing to provide a graspable portion. When the stretch release adhesive is adhered between the electrical component and the internal surface of the housing, the stretch release adhesive can receive a pulling force at the graspable portion. If pulled with enough force, the stretch release adhesive will extend outwardly from between the electrical component and the internal surface of the mobile computing device, then completely release the electrical component from the mobile computing device.   \n",
       "17                              An installation assembly and an associated method for forming a bonded join are provided to permit the adhesive attachment of a first workpiece, such as a patch, to a portion of a second workpiece. The installation assembly and the associated method provide for at least partial debulking of the adhesive prior to curing of the adhesive such that the resulting bondline may have improved mechanical properties as a result of having fewer voids and/or porosity. The installation assembly may include an installation stand and a carrier plate supported by the installation stand and including an attachment surface configured to carry the first workpiece. The installation stand also includes an adjustment mechanism for positioning a carrier plate to a first predefined position to define a gap between the first and second workpieces and also to a second predefined position such that a predetermined bondline thickness is defined between the first and second workpieces.   \n",
       "18                                                                                                                                                                                                                              A three-dimensional object printer enables forming portions of an object with a material having a higher melting temperature and a lower coefficient of friction. The printer includes a member, a printhead, and an applicator. A controller operates the printhead to eject a first material having a first coefficient of friction toward the member and operates the applicator to eject a second material having a second coefficient of friction toward the member. The second material has a higher melting temperature and a lower coefficient of friction than the first material. The printer further includes a curing device. The controller operates the curing device to direct radiation toward the member to cure the first material. The second material is cured into the first material.   \n",
       "19                                                                                                                                                                                                                                                    There is provided a method for manufacturing a three-dimensional shaped object. The method of the present invention comprises the repeated steps of: (i) forming a solidified layer by irradiating a predetermined portion of a powder layer with a light beam, thereby allowing a sintering of the powder in the predetermined portion or a melting and subsequent solidification thereof; and (ii) forming another solidified layer by newly forming a powder layer on the resulting solidified layer, followed by the irradiation of a predetermined portion of the powder layer with the light beam; wherein only the surface portion of the solidified layer, to which a force is applied when the three-dimensional shaped object is used, is subjected to a machining process.   \n",
       "\n",
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      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_patent = pd.read_csv(\"g_patent.tsv\", delimiter='\\t', dtype={'patent_id': str, \n",
    "                                                        'patent_type': str, \n",
    "                                                        'patent_title': str,\n",
    "                                                        'patent_abstract': str,\n",
    "                                                        'wipo_kind': str,\n",
    "                                                        'num_claims': int,\n",
    "                                                        'withdrawn': int,\n",
    "                                                        'filename': str}, parse_dates=[2])\n",
    "df_patent.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9540605d",
   "metadata": {
    "tags": []
   },
   "outputs": [
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       "1    10913199             0           B       B29         B29C      B29C55/08   \n",
       "2     5208443             0           B       B29         B29C     B29C65/366   \n",
       "3     7830588             6           G       G09         G09G  G09G2310/0275   \n",
       "4     7232943             1           A       A01         A01H       A01H5/10   \n",
       "5    10815370             2           C       C08         C08F     C08F265/08   \n",
       "6     8271025             4           H       H04         H04M      H04M15/00   \n",
       "7     8208778             1           G       G02         G02B    G02B6/12002   \n",
       "8    10299603            18           B       B64         B64D   B64D11/00154   \n",
       "9    10941581            24           B       B32         B32B    B32B2255/10   \n",
       "10    7961343            29           G       G06         G06K      G06K15/02   \n",
       "11    9679483             1           B       B60         B60K    B60K31/0058   \n",
       "12   10095625             0           G       G06         G06F    G06F12/0866   \n",
       "13   11074220             4           G       G06         G06F     G06F3/0608   \n",
       "14    7029271             5           Y       Y02         Y02E      Y02E20/34   \n",
       "15    4068035             9           Y       Y10         Y10S    Y10S528/904   \n",
       "16   10536024             1           H       H02         H02J       H02J7/00   \n",
       "17    8617927            17           H       H01         H01L      H01L25/16   \n",
       "18    6633281             7           H       H04         H04B      H04B1/202   \n",
       "19    9656935             0           C       C07         C07C      C07C41/28   \n",
       "\n",
       "       cpc_type cpc_symbol_position  \n",
       "0   inventional                 NaN  \n",
       "1   inventional                 NaN  \n",
       "2   inventional                 NaN  \n",
       "3    additional                 NaN  \n",
       "4   inventional                 NaN  \n",
       "5   inventional                 NaN  \n",
       "6   inventional                 NaN  \n",
       "7   inventional                 NaN  \n",
       "8   inventional                 NaN  \n",
       "9    additional                 NaN  \n",
       "10  inventional                 NaN  \n",
       "11  inventional                 NaN  \n",
       "12  inventional                 NaN  \n",
       "13  inventional                 NaN  \n",
       "14   additional                 NaN  \n",
       "15   additional                 NaN  \n",
       "16  inventional                 NaN  \n",
       "17  inventional                 NaN  \n",
       "18   additional                 NaN  \n",
       "19  inventional                 NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cpc = pd.read_table(\"g_cpc_current.tsv\", delimiter=\"\\t\", dtype={\"patent_id\": int,\n",
    "                                                               \"cpc_sequence\": int,\n",
    "                                                               \"cpc_section\": str,\n",
    "                                                               \"cpc_subclass\": str,\n",
    "                                                               \"cpc_group\": str,\n",
    "                                                               \"cpc_type\": str,\n",
    "                                                               \"cpc_symbol_position\": str})\n",
    "df_cpc.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "788bf50b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>population</th>\n",
       "      <th>labor_force</th>\n",
       "      <th>population_percent</th>\n",
       "      <th>employed_total</th>\n",
       "      <th>employed_percent</th>\n",
       "      <th>agrictulture_ratio</th>\n",
       "      <th>nonagriculture_ratio</th>\n",
       "      <th>unemployed</th>\n",
       "      <th>unemployed_percent</th>\n",
       "      <th>not_in_labor</th>\n",
       "      <th>footnotes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>156150</td>\n",
       "      <td>96158</td>\n",
       "      <td>61.6</td>\n",
       "      <td>88752</td>\n",
       "      <td>56.8</td>\n",
       "      <td>3331</td>\n",
       "      <td>85421</td>\n",
       "      <td>7406</td>\n",
       "      <td>7.7</td>\n",
       "      <td>59991</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>159033</td>\n",
       "      <td>99008</td>\n",
       "      <td>62.3</td>\n",
       "      <td>92017</td>\n",
       "      <td>57.9</td>\n",
       "      <td>3283</td>\n",
       "      <td>88734</td>\n",
       "      <td>6991</td>\n",
       "      <td>7.1</td>\n",
       "      <td>60025</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>161910</td>\n",
       "      <td>102250</td>\n",
       "      <td>63.2</td>\n",
       "      <td>96048</td>\n",
       "      <td>59.3</td>\n",
       "      <td>3387</td>\n",
       "      <td>92661</td>\n",
       "      <td>6202</td>\n",
       "      <td>6.1</td>\n",
       "      <td>59659</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1979</th>\n",
       "      <td>164863</td>\n",
       "      <td>104962</td>\n",
       "      <td>63.7</td>\n",
       "      <td>98824</td>\n",
       "      <td>59.9</td>\n",
       "      <td>3347</td>\n",
       "      <td>95477</td>\n",
       "      <td>6137</td>\n",
       "      <td>5.8</td>\n",
       "      <td>59900</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1980</th>\n",
       "      <td>167745</td>\n",
       "      <td>106940</td>\n",
       "      <td>63.8</td>\n",
       "      <td>99302</td>\n",
       "      <td>59.2</td>\n",
       "      <td>3364</td>\n",
       "      <td>95938</td>\n",
       "      <td>7637</td>\n",
       "      <td>7.1</td>\n",
       "      <td>60806</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>170130</td>\n",
       "      <td>108670</td>\n",
       "      <td>63.9</td>\n",
       "      <td>100397</td>\n",
       "      <td>59.0</td>\n",
       "      <td>3368</td>\n",
       "      <td>97030</td>\n",
       "      <td>8273</td>\n",
       "      <td>7.6</td>\n",
       "      <td>61460</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>172271</td>\n",
       "      <td>110204</td>\n",
       "      <td>64.0</td>\n",
       "      <td>99526</td>\n",
       "      <td>57.8</td>\n",
       "      <td>3401</td>\n",
       "      <td>96125</td>\n",
       "      <td>10678</td>\n",
       "      <td>9.7</td>\n",
       "      <td>62067</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>174215</td>\n",
       "      <td>111550</td>\n",
       "      <td>64.0</td>\n",
       "      <td>100834</td>\n",
       "      <td>57.9</td>\n",
       "      <td>3383</td>\n",
       "      <td>97450</td>\n",
       "      <td>10717</td>\n",
       "      <td>9.6</td>\n",
       "      <td>62665</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>176383</td>\n",
       "      <td>113544</td>\n",
       "      <td>64.4</td>\n",
       "      <td>105005</td>\n",
       "      <td>59.5</td>\n",
       "      <td>3321</td>\n",
       "      <td>101685</td>\n",
       "      <td>8539</td>\n",
       "      <td>7.5</td>\n",
       "      <td>62839</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>178206</td>\n",
       "      <td>115461</td>\n",
       "      <td>64.8</td>\n",
       "      <td>107150</td>\n",
       "      <td>60.1</td>\n",
       "      <td>3179</td>\n",
       "      <td>103971</td>\n",
       "      <td>8312</td>\n",
       "      <td>7.2</td>\n",
       "      <td>62744</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>180587</td>\n",
       "      <td>117834</td>\n",
       "      <td>65.3</td>\n",
       "      <td>109597</td>\n",
       "      <td>60.7</td>\n",
       "      <td>3163</td>\n",
       "      <td>106434</td>\n",
       "      <td>8237</td>\n",
       "      <td>7.0</td>\n",
       "      <td>62752</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>182753</td>\n",
       "      <td>119865</td>\n",
       "      <td>65.6</td>\n",
       "      <td>112440</td>\n",
       "      <td>61.5</td>\n",
       "      <td>3208</td>\n",
       "      <td>109232</td>\n",
       "      <td>7425</td>\n",
       "      <td>6.2</td>\n",
       "      <td>62888</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>184613</td>\n",
       "      <td>121669</td>\n",
       "      <td>65.9</td>\n",
       "      <td>114968</td>\n",
       "      <td>62.3</td>\n",
       "      <td>3169</td>\n",
       "      <td>111800</td>\n",
       "      <td>6701</td>\n",
       "      <td>5.5</td>\n",
       "      <td>62944</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>186393</td>\n",
       "      <td>123869</td>\n",
       "      <td>66.5</td>\n",
       "      <td>117342</td>\n",
       "      <td>63.0</td>\n",
       "      <td>3199</td>\n",
       "      <td>114142</td>\n",
       "      <td>6528</td>\n",
       "      <td>5.3</td>\n",
       "      <td>62523</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>189164</td>\n",
       "      <td>125840</td>\n",
       "      <td>66.5</td>\n",
       "      <td>118793</td>\n",
       "      <td>62.8</td>\n",
       "      <td>3223</td>\n",
       "      <td>115570</td>\n",
       "      <td>7047</td>\n",
       "      <td>5.6</td>\n",
       "      <td>63324</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>190925</td>\n",
       "      <td>126346</td>\n",
       "      <td>66.2</td>\n",
       "      <td>117718</td>\n",
       "      <td>61.7</td>\n",
       "      <td>3269</td>\n",
       "      <td>114449</td>\n",
       "      <td>8628</td>\n",
       "      <td>6.8</td>\n",
       "      <td>64578</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>192805</td>\n",
       "      <td>128105</td>\n",
       "      <td>66.4</td>\n",
       "      <td>118492</td>\n",
       "      <td>61.5</td>\n",
       "      <td>3247</td>\n",
       "      <td>115245</td>\n",
       "      <td>9613</td>\n",
       "      <td>7.5</td>\n",
       "      <td>64700</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>194838</td>\n",
       "      <td>129200</td>\n",
       "      <td>66.3</td>\n",
       "      <td>120259</td>\n",
       "      <td>61.7</td>\n",
       "      <td>3115</td>\n",
       "      <td>117144</td>\n",
       "      <td>8940</td>\n",
       "      <td>6.9</td>\n",
       "      <td>65638</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>196814</td>\n",
       "      <td>131056</td>\n",
       "      <td>66.6</td>\n",
       "      <td>123060</td>\n",
       "      <td>62.5</td>\n",
       "      <td>3409</td>\n",
       "      <td>119651</td>\n",
       "      <td>7996</td>\n",
       "      <td>6.1</td>\n",
       "      <td>65758</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>198584</td>\n",
       "      <td>132304</td>\n",
       "      <td>66.6</td>\n",
       "      <td>124900</td>\n",
       "      <td>62.9</td>\n",
       "      <td>3440</td>\n",
       "      <td>121460</td>\n",
       "      <td>7404</td>\n",
       "      <td>5.6</td>\n",
       "      <td>66280</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>200591</td>\n",
       "      <td>133943</td>\n",
       "      <td>66.8</td>\n",
       "      <td>126708</td>\n",
       "      <td>63.2</td>\n",
       "      <td>3443</td>\n",
       "      <td>123264</td>\n",
       "      <td>7236</td>\n",
       "      <td>5.4</td>\n",
       "      <td>66647</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>203133</td>\n",
       "      <td>136297</td>\n",
       "      <td>67.1</td>\n",
       "      <td>129558</td>\n",
       "      <td>63.8</td>\n",
       "      <td>3399</td>\n",
       "      <td>126159</td>\n",
       "      <td>6739</td>\n",
       "      <td>4.9</td>\n",
       "      <td>66836</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>205220</td>\n",
       "      <td>137673</td>\n",
       "      <td>67.1</td>\n",
       "      <td>131463</td>\n",
       "      <td>64.1</td>\n",
       "      <td>3378</td>\n",
       "      <td>128085</td>\n",
       "      <td>6210</td>\n",
       "      <td>4.5</td>\n",
       "      <td>67547</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>207753</td>\n",
       "      <td>139368</td>\n",
       "      <td>67.1</td>\n",
       "      <td>133488</td>\n",
       "      <td>64.3</td>\n",
       "      <td>3281</td>\n",
       "      <td>130207</td>\n",
       "      <td>5880</td>\n",
       "      <td>4.2</td>\n",
       "      <td>68385</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>212577</td>\n",
       "      <td>142583</td>\n",
       "      <td>67.1</td>\n",
       "      <td>136891</td>\n",
       "      <td>64.4</td>\n",
       "      <td>2464</td>\n",
       "      <td>134427</td>\n",
       "      <td>5692</td>\n",
       "      <td>4.0</td>\n",
       "      <td>69994</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>215092</td>\n",
       "      <td>143734</td>\n",
       "      <td>66.8</td>\n",
       "      <td>136933</td>\n",
       "      <td>63.7</td>\n",
       "      <td>2299</td>\n",
       "      <td>134635</td>\n",
       "      <td>6801</td>\n",
       "      <td>4.7</td>\n",
       "      <td>71359</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>217570</td>\n",
       "      <td>144863</td>\n",
       "      <td>66.6</td>\n",
       "      <td>136485</td>\n",
       "      <td>62.7</td>\n",
       "      <td>2311</td>\n",
       "      <td>134174</td>\n",
       "      <td>8378</td>\n",
       "      <td>5.8</td>\n",
       "      <td>72707</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>221168</td>\n",
       "      <td>146510</td>\n",
       "      <td>66.2</td>\n",
       "      <td>137736</td>\n",
       "      <td>62.3</td>\n",
       "      <td>2275</td>\n",
       "      <td>135461</td>\n",
       "      <td>8774</td>\n",
       "      <td>6.0</td>\n",
       "      <td>74658</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>223357</td>\n",
       "      <td>147401</td>\n",
       "      <td>66.0</td>\n",
       "      <td>139252</td>\n",
       "      <td>62.3</td>\n",
       "      <td>2232</td>\n",
       "      <td>137020</td>\n",
       "      <td>8149</td>\n",
       "      <td>5.5</td>\n",
       "      <td>75956</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>226082</td>\n",
       "      <td>149320</td>\n",
       "      <td>66.0</td>\n",
       "      <td>141730</td>\n",
       "      <td>62.7</td>\n",
       "      <td>2197</td>\n",
       "      <td>139532</td>\n",
       "      <td>7591</td>\n",
       "      <td>5.1</td>\n",
       "      <td>76762</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>228815</td>\n",
       "      <td>151428</td>\n",
       "      <td>66.2</td>\n",
       "      <td>144427</td>\n",
       "      <td>63.1</td>\n",
       "      <td>2206</td>\n",
       "      <td>142221</td>\n",
       "      <td>7001</td>\n",
       "      <td>4.6</td>\n",
       "      <td>77387</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>231867</td>\n",
       "      <td>153124</td>\n",
       "      <td>66.0</td>\n",
       "      <td>146047</td>\n",
       "      <td>63.0</td>\n",
       "      <td>2095</td>\n",
       "      <td>143952</td>\n",
       "      <td>7078</td>\n",
       "      <td>4.6</td>\n",
       "      <td>78743</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>233788</td>\n",
       "      <td>154287</td>\n",
       "      <td>66.0</td>\n",
       "      <td>145362</td>\n",
       "      <td>62.2</td>\n",
       "      <td>2168</td>\n",
       "      <td>143194</td>\n",
       "      <td>8924</td>\n",
       "      <td>5.8</td>\n",
       "      <td>79501</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>235801</td>\n",
       "      <td>154142</td>\n",
       "      <td>65.4</td>\n",
       "      <td>139877</td>\n",
       "      <td>59.3</td>\n",
       "      <td>2103</td>\n",
       "      <td>137775</td>\n",
       "      <td>14265</td>\n",
       "      <td>9.3</td>\n",
       "      <td>81659</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>237830</td>\n",
       "      <td>153889</td>\n",
       "      <td>64.7</td>\n",
       "      <td>139064</td>\n",
       "      <td>58.5</td>\n",
       "      <td>2206</td>\n",
       "      <td>136858</td>\n",
       "      <td>14825</td>\n",
       "      <td>9.6</td>\n",
       "      <td>83941</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      population  labor_force  population_percent  employed_total  \\\n",
       "year                                                                \n",
       "1976      156150        96158                61.6           88752   \n",
       "1977      159033        99008                62.3           92017   \n",
       "1978      161910       102250                63.2           96048   \n",
       "1979      164863       104962                63.7           98824   \n",
       "1980      167745       106940                63.8           99302   \n",
       "1981      170130       108670                63.9          100397   \n",
       "1982      172271       110204                64.0           99526   \n",
       "1983      174215       111550                64.0          100834   \n",
       "1984      176383       113544                64.4          105005   \n",
       "1985      178206       115461                64.8          107150   \n",
       "1986      180587       117834                65.3          109597   \n",
       "1987      182753       119865                65.6          112440   \n",
       "1988      184613       121669                65.9          114968   \n",
       "1989      186393       123869                66.5          117342   \n",
       "1990      189164       125840                66.5          118793   \n",
       "1991      190925       126346                66.2          117718   \n",
       "1992      192805       128105                66.4          118492   \n",
       "1993      194838       129200                66.3          120259   \n",
       "1994      196814       131056                66.6          123060   \n",
       "1995      198584       132304                66.6          124900   \n",
       "1996      200591       133943                66.8          126708   \n",
       "1997      203133       136297                67.1          129558   \n",
       "1998      205220       137673                67.1          131463   \n",
       "1999      207753       139368                67.1          133488   \n",
       "2000      212577       142583                67.1          136891   \n",
       "2001      215092       143734                66.8          136933   \n",
       "2002      217570       144863                66.6          136485   \n",
       "2003      221168       146510                66.2          137736   \n",
       "2004      223357       147401                66.0          139252   \n",
       "2005      226082       149320                66.0          141730   \n",
       "2006      228815       151428                66.2          144427   \n",
       "2007      231867       153124                66.0          146047   \n",
       "2008      233788       154287                66.0          145362   \n",
       "2009      235801       154142                65.4          139877   \n",
       "2010      237830       153889                64.7          139064   \n",
       "\n",
       "      employed_percent  agrictulture_ratio  nonagriculture_ratio  unemployed  \\\n",
       "year                                                                           \n",
       "1976              56.8                3331                 85421        7406   \n",
       "1977              57.9                3283                 88734        6991   \n",
       "1978              59.3                3387                 92661        6202   \n",
       "1979              59.9                3347                 95477        6137   \n",
       "1980              59.2                3364                 95938        7637   \n",
       "1981              59.0                3368                 97030        8273   \n",
       "1982              57.8                3401                 96125       10678   \n",
       "1983              57.9                3383                 97450       10717   \n",
       "1984              59.5                3321                101685        8539   \n",
       "1985              60.1                3179                103971        8312   \n",
       "1986              60.7                3163                106434        8237   \n",
       "1987              61.5                3208                109232        7425   \n",
       "1988              62.3                3169                111800        6701   \n",
       "1989              63.0                3199                114142        6528   \n",
       "1990              62.8                3223                115570        7047   \n",
       "1991              61.7                3269                114449        8628   \n",
       "1992              61.5                3247                115245        9613   \n",
       "1993              61.7                3115                117144        8940   \n",
       "1994              62.5                3409                119651        7996   \n",
       "1995              62.9                3440                121460        7404   \n",
       "1996              63.2                3443                123264        7236   \n",
       "1997              63.8                3399                126159        6739   \n",
       "1998              64.1                3378                128085        6210   \n",
       "1999              64.3                3281                130207        5880   \n",
       "2000              64.4                2464                134427        5692   \n",
       "2001              63.7                2299                134635        6801   \n",
       "2002              62.7                2311                134174        8378   \n",
       "2003              62.3                2275                135461        8774   \n",
       "2004              62.3                2232                137020        8149   \n",
       "2005              62.7                2197                139532        7591   \n",
       "2006              63.1                2206                142221        7001   \n",
       "2007              63.0                2095                143952        7078   \n",
       "2008              62.2                2168                143194        8924   \n",
       "2009              59.3                2103                137775       14265   \n",
       "2010              58.5                2206                136858       14825   \n",
       "\n",
       "      unemployed_percent  not_in_labor  footnotes  \n",
       "year                                               \n",
       "1976                 7.7         59991        NaN  \n",
       "1977                 7.1         60025        NaN  \n",
       "1978                 6.1         59659        1.0  \n",
       "1979                 5.8         59900        NaN  \n",
       "1980                 7.1         60806        NaN  \n",
       "1981                 7.6         61460        NaN  \n",
       "1982                 9.7         62067        NaN  \n",
       "1983                 9.6         62665        NaN  \n",
       "1984                 7.5         62839        NaN  \n",
       "1985                 7.2         62744        NaN  \n",
       "1986                 7.0         62752        1.0  \n",
       "1987                 6.2         62888        NaN  \n",
       "1988                 5.5         62944        NaN  \n",
       "1989                 5.3         62523        NaN  \n",
       "1990                 5.6         63324        1.0  \n",
       "1991                 6.8         64578        NaN  \n",
       "1992                 7.5         64700        NaN  \n",
       "1993                 6.9         65638        NaN  \n",
       "1994                 6.1         65758        1.0  \n",
       "1995                 5.6         66280        NaN  \n",
       "1996                 5.4         66647        NaN  \n",
       "1997                 4.9         66836        1.0  \n",
       "1998                 4.5         67547        1.0  \n",
       "1999                 4.2         68385        1.0  \n",
       "2000                 4.0         69994        1.0  \n",
       "2001                 4.7         71359        NaN  \n",
       "2002                 5.8         72707        NaN  \n",
       "2003                 6.0         74658        1.0  \n",
       "2004                 5.5         75956        1.0  \n",
       "2005                 5.1         76762        1.0  \n",
       "2006                 4.6         77387        1.0  \n",
       "2007                 4.6         78743        1.0  \n",
       "2008                 5.8         79501        1.0  \n",
       "2009                 9.3         81659        1.0  \n",
       "2010                 9.6         83941        1.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_unemployment = pd.read_csv(\"aat1.csv\", skiprows=range(1,37))\n",
    "df_unemployment.set_index('year', inplace=True)\n",
    "# df_unemployment.drop(inplace=True,columns=df_unemployment.columns[:8])\n",
    "# df_unemployment.drop(inplace=True,columns=df_unemployment.columns[1:])\n",
    "df_unemployment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "efa185a3",
   "metadata": {},
   "outputs": [],
   "source": [
    "ppy = df_patent.groupby([df_patent['patent_date'].dt.year.rename('year')]).agg({'count'}).iloc[:-12]\n",
    "ppy.drop(inplace=True, columns=ppy.columns[:-1])\n",
    "ppy['filename']['count'] = ppy['filename']['count'].astype(int)\n",
    "ppy['filename']['count'].div(1000)\n",
    "ppy = ppy['filename']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "a7bb7ab2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Comparing Patents Per Year and Unemployment Percent'}, xlabel='Year', ylabel='Patents Per 10k /Unemployment percentage'>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = ppy.div(10000).plot()\n",
    "ax = df_unemployment.plot(ax=ax, lw=2, colormap='jet', marker='.', markersize=10, title='Comparing Patents Per Year and Unemployment Percent')\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Patents Per 10k /Unemployment percentage\")\n",
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "6253e992",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Comparing Granted Patents Per Year and The Population Number in thousands of the USA'}, xlabel='Year', ylabel='Patents Per Year / Population Size of America'>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_unemployment = pd.read_csv(\"aat1.csv\", skiprows=range(1,37))\n",
    "df_unemployment.set_index('year', inplace=True)\n",
    "df_unemployment.drop(inplace=True, columns=df_unemployment.columns[1:])\n",
    "ppy = df_patent.groupby([df_patent['patent_date'].dt.year.rename('year')]).agg({'count'}).iloc[:-12]\n",
    "ppy.drop(inplace=True, columns=ppy.columns[:-1])\n",
    "ppy['filename']['count'] = ppy['filename']['count'].astype(int)\n",
    "ppy['filename']['count'].div(1000)\n",
    "ppy = ppy['filename']\n",
    "ax = ppy.plot()\n",
    "ax = df_unemployment.plot(ax=ax, lw=2, colormap='jet', marker='.', markersize=10, title='Comparing Granted Patents Per Year and The Population Number in thousands of the USA')\n",
    "ax.set(xlabel=\"Year\", ylabel=\"Patents Per Year / Population Size of America\")\n",
    "ax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "601005ca",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}