exercise-choosing-plot-types-and-custom-styles.ipynb

{"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"**This notebook is an exercise in the [Data Visualization](https://www.kaggle.com/learn/data-visualization) course.  You can reference the tutorial at [this link](https://www.kaggle.com/alexisbcook/choosing-plot-types-and-custom-styles).**\n\n---\n","metadata":{}},{"cell_type":"markdown","source":"In this exercise, you'll explore different chart styles, to see which color combinations and fonts you like best!\n\n## Setup\n\nRun the next cell to import and configure the Python libraries that you need to complete the exercise.","metadata":{}},{"cell_type":"code","source":"import pandas as pd\npd.plotting.register_matplotlib_converters()\nimport matplotlib.pyplot as plt\n%matplotlib inline\nimport seaborn as sns\nprint(\"Setup Complete\")","metadata":{"execution":{"iopub.status.busy":"2022-10-31T08:54:20.022858Z","iopub.execute_input":"2022-10-31T08:54:20.023432Z","iopub.status.idle":"2022-10-31T08:54:21.093272Z","shell.execute_reply.started":"2022-10-31T08:54:20.023311Z","shell.execute_reply":"2022-10-31T08:54:21.091954Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stdout","text":"Setup Complete\n","output_type":"stream"}]},{"cell_type":"markdown","source":"The questions below will give you feedback on your work. Run the following cell to set up our feedback system.","metadata":{}},{"cell_type":"code","source":"# Set up code checking\nimport os\nif not os.path.exists(\"../input/spotify.csv\"):\n    os.symlink(\"../input/data-for-datavis/spotify.csv\", \"../input/spotify.csv\") \nfrom learntools.core import binder\nbinder.bind(globals())\nfrom learntools.data_viz_to_coder.ex6 import *\nprint(\"Setup Complete\")","metadata":{"execution":{"iopub.status.busy":"2022-10-31T08:54:21.095218Z","iopub.execute_input":"2022-10-31T08:54:21.095654Z","iopub.status.idle":"2022-10-31T08:54:21.145628Z","shell.execute_reply.started":"2022-10-31T08:54:21.095618Z","shell.execute_reply":"2022-10-31T08:54:21.144700Z"},"trusted":true},"execution_count":2,"outputs":[{"name":"stdout","text":"Setup Complete\n","output_type":"stream"}]},{"cell_type":"markdown","source":"You'll work with a chart from the previous tutorial.  Run the next cell to load the data.","metadata":{}},{"cell_type":"code","source":"# Path of the file to read\nspotify_filepath = \"../input/spotify.csv\"\n\n# Read the file into a variable spotify_data\nspotify_data = pd.read_csv(spotify_filepath, index_col=\"Date\", parse_dates=True)","metadata":{"execution":{"iopub.status.busy":"2022-10-31T08:54:30.330255Z","iopub.execute_input":"2022-10-31T08:54:30.330735Z","iopub.status.idle":"2022-10-31T08:54:30.356929Z","shell.execute_reply.started":"2022-10-31T08:54:30.330692Z","shell.execute_reply":"2022-10-31T08:54:30.356053Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"markdown","source":"# Try out seaborn styles\n\nRun the command below to try out the `\"dark\"` theme.","metadata":{}},{"cell_type":"code","source":"# Change the style of the figure\nsns.set_style(\"dark\")\n\n# Line chart \nplt.figure(figsize=(12,6))\nsns.lineplot(data=spotify_data)\n\n# Mark the exercise complete after the code cell is run\nstep_1.check()","metadata":{},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now, try out different themes by amending the first line of code and running the code cell again.  Remember the list of available themes:\n- `\"darkgrid\"`\n- `\"whitegrid\"`\n- `\"dark\"`\n- `\"white\"`\n- `\"ticks\"`\n\nThis notebook is your playground -- feel free to experiment as little or as much you wish here!  The exercise is marked as complete after you run every code cell in the notebook at least once.\n\n## Keep going\n\nLearn about how to select and visualize your own datasets in the **[next tutorial](https://www.kaggle.com/alexisbcook/final-project)**!","metadata":{}},{"cell_type":"markdown","source":"---\n\n\n\n\n*Have questions or comments? Visit the [course discussion forum](https://www.kaggle.com/learn/data-visualization/discussion) to chat with other learners.*","metadata":{}}]}