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Sphinx RST File Modification - Added QueryProfiler (#900)
* Added QueryProfiler in RST * added okwarning for regexp warnings * fixed geo import * fixed regexp in docstring * fixed geo function backslash * fixed text backslash * fixed backslash for preprocessing * resolving import * comments * add warning for vdataframe text * fixing preprocessing * Update functions.py * small corrections * Update _scaler.py --------- Co-authored-by: Badr <badr.ouali@outlook.fr>
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‎docs/source/utilities.rst

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@@ -6,6 +6,38 @@ Utilities
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______
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Performance
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-------------
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Query Performance
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^^^^^^^^^^^^^^^^^^
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.. currentmodule:: verticapy.performance.vertica.qprof
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.. autosummary::
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:toctree: api/
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QueryProfiler
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.. currentmodule:: verticapy.performance.vertica.qprof
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**Methods:**
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.. autosummary::
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:toctree: api/
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QueryProfiler.get_cluster_config
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QueryProfiler.get_cpu_time
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QueryProfiler.get_qduration
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QueryProfiler.get_qexecution
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QueryProfiler.get_qexecution_report
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QueryProfiler.get_qplan
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QueryProfiler.get_qplan_profile
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QueryProfiler.get_qsteps
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QueryProfiler.get_request
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QueryProfiler.get_rp_status
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QueryProfiler.get_version
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QueryProfiler.step
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Options & Displaying

‎verticapy/core/vdataframe/_plotting_animated.py

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@@ -92,7 +92,7 @@ def animated_bar(
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If set to True, the animation is repeated.
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chart: PlottingObject, optional
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The chart object used to plot.
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\*\*style_kwargs
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**style_kwargs
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Any optional parameter to pass to the plotting functions.
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Returns
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If set to True, the animation is repeated.
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chart: PlottingObject, optional
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The chart object used to plot.
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\*\*style_kwargs
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**style_kwargs
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Any optional parameter to pass to the plotting functions.
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Returns
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If set to True, the animation is repeated.
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chart: PlottingObject, optional
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The chart object used to plot.
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\*\*style_kwargs
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**style_kwargs
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Any optional parameter to pass to the plotting
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functions.
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@@ -554,7 +554,7 @@ def animated_scatter(
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If set to True, the animation is repeated.
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chart: PlottingObject, optional
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The chart object used to plot.
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\*\*style_kwargs
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**style_kwargs
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Any optional parameter to pass to the plotting
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functions.
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‎verticapy/core/vdataframe/_scaler.py

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@@ -55,21 +55,21 @@ def scale(
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.. math::
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Z\_score(x) = (x - x_{avg}) / x_{std}
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Z_{score}(x) = (x - x_{avg}) / x_{std}
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- robust_zscore:
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Normalization using the Robust Z-Score.
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.. math::
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Z\_rscore(x) = (x - x_{med}) / (1.4826 * x_{mad})
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Z_{rscore}(x) = (x - x_{med}) / (1.4826 * x_{mad})
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- minmax:
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Normalization using the MinMax.
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.. math::
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Z\_minmax(x) = (x - x_{min}) / (x_{max} - x_{min})
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Z_{minmax}(x) = (x - x_{min}) / (x_{max} - x_{min})
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Returns
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-------
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.. math::
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Z\_score(x) = (x - x_{avg}) / x_{std}
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Z_{score}(x) = (x - x_{avg}) / x_{std}
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- robust_zscore:
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Normalization using the Robust Z-Score.
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.. math::
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Z\_rscore(x) = (x - x_{med}) / (1.4826 * x_{mad})
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Z_{rscore}(x) = (x - x_{med}) / (1.4826 * x_{mad})
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- minmax:
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Normalization using the MinMax.
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.. math::
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Z\_minmax(x) = (x - x_{min}) / (x_{max} - x_{min})
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Z_{minmax}(x) = (x - x_{min}) / (x_{max} - x_{min})
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by: SQLColumns, optional
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vDataColumns used in the partition.
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return_trans: bool, optimal

‎verticapy/core/vdataframe/_text.py

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@@ -432,12 +432,13 @@ def str_extract(self, pat: str) -> "vDataFrame":
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.. code-block:: python
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data["name"].str_extract(pat = "([A-Za-z])+\.")
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data["name"].str_extract(pat = "([A-Za-z])+\\.")
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.. ipython:: python
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:suppress:
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:okwarning:
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res = data["name"].str_extract(pat = "([A-Za-z])+\.")
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res = data["name"].str_extract(pat = "([A-Za-z])+\\.")
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html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_text_str_extract.html", "w")
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html_file.write(res._repr_html_())
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html_file.close()
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.. code-block:: python
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data["name"].str_replace(
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to_replace = "([A-Za-z])+\.",
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to_replace = "([A-Za-z])+\\.",
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value = "[Name_Prefix]"
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)
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.. ipython:: python
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:suppress:
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:okwarning:
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res = data["name"].str_replace(
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to_replace = "([A-Za-z])+\.",
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to_replace = "([A-Za-z])+\\.",
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value = "[Name_Prefix]"
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)
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html_file = open("SPHINX_DIRECTORY/figures/core_vDataFrame_text_str_replace.html", "w")

‎verticapy/core/vdataframe/_utils.py

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@@ -69,7 +69,7 @@ def format_colnames(
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Parameters
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----------
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\*args: str / list / dict, optional
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*args: str / list / dict, optional
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List of columns' names to format. This allows you
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to use multiple objects as input and to format all
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of them.

‎verticapy/machine_learning/memmodel/ensemble.py

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tree_id: int, optional
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Unique tree identifier, an integer in the
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range [0, n_estimators - 1].
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\*args, \*\*kwargs: Any, optional
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*args, **kwargs: Any, optional
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Arguments to pass to the 'to_graphviz' method.
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Returns

‎verticapy/machine_learning/memmodel/preprocessing.py

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Parameters
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----------
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min\_: ArrayLike
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min_: ArrayLike
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Model's features minimums.
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max\_: ArrayLike
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max_: ArrayLike
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Model's features maximums.
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.. note::

‎verticapy/machine_learning/memmodel/tree.py

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----------
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pic_path: str, optional
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Absolute path to save the image of the tree.
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\*args, \*\*kwargs: Any, optional
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*args, **kwargs: Any, optional
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Arguments to pass to the 'to_graphviz' method.
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Returns

‎verticapy/machine_learning/vertica/preprocessing.py

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----------
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Many attributes are created during the fitting phase.
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**For ``StandardScaler``:**
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**For StandardScaler:**
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mean_: numpy.array
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Model's features means.
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std_: numpy.array
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Model's features standard deviation.
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**For ``MinMaxScaler``:**
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**For MinMaxScaler:**
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min_: numpy.array
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Model's features minimums.
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max_: numpy.array
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Model's features maximums.
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**For ``RobustScaler``:**
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**For RobustScaler:**
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median_: numpy.array
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Model's features medians.

‎verticapy/sql/functions/regexp.py

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titanic = load_titanic()
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# Apply the regexp_count function, creating a new "has_title" column
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titanic["has_title"] = vpf.regexp_count(titanic["name"], '([A-Za-z])+\. ')
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titanic["has_title"] = vpf.regexp_count(titanic["name"], '([A-Za-z])+\\.')
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display(titanic[["name", "has_title"]])
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.. ipython:: python
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:suppress:
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from verticapy.datasets import load_titanic
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import verticapy.sql.functions as vpf
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titanic = load_titanic()
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titanic["has_title"] = vpf.regexp_count(titanic["name"], '([A-Za-z])+\. ')
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titanic["has_title"] = vpf.regexp_count(titanic["name"], '([A-Za-z])+\\.')
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_count.html", "w")
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html_file.write(titanic[["name", "has_title"]]._repr_html_())
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# Apply the regexp_ilike function, creating a new "has_title" column
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titanic["has_title"] = vpf.regexp_ilike(titanic["name"], '([A-Za-z])+\. ')
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titanic["has_title"] = vpf.regexp_ilike(titanic["name"], '([A-Za-z])+\\.')
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display(titanic[["name", "has_title"]])
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.. ipython:: python
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:suppress:
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:okwarning:
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from verticapy.datasets import load_titanic
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import verticapy.sql.functions as vpf
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titanic = load_titanic()
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titanic["has_title"] = vpf.regexp_ilike(titanic["name"], '([A-Za-z])+\. ')
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titanic["has_title"] = vpf.regexp_ilike(titanic["name"], '([A-Za-z])+\\.')
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_ilike.html", "w")
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html_file.write(titanic[["name", "has_title"]]._repr_html_())
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titanic["title_start"] = vpf.regexp_instr(titanic["name"],
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'([A-Za-z])+\. ',
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'([A-Za-z])+\\.',
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return_position = 0)
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display(titanic[["name", "title_start"]])
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.. ipython:: python
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:okwarning:
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import verticapy.sql.functions as vpf
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titanic = load_titanic()
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titanic["title_start"] = vpf.regexp_instr(titanic["name"], '([A-Za-z])+\. ', return_position = 0)
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titanic["title_start"] = vpf.regexp_instr(titanic["name"], '([A-Za-z])+\\.', return_position = 0)
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_instr.html", "w")
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html_file.write(titanic[["name", "title_start"]]._repr_html_())
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# Apply the regexp_like function, creating a new "has_title" column
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titanic["has_title"] = vpf.regexp_like(titanic["name"], '([A-Za-z])+\. ')
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titanic["has_title"] = vpf.regexp_like(titanic["name"], '([A-Za-z])+\\.')
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display(titanic[["name", "has_title"]])
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.. ipython:: python
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:suppress:
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:okwarning:
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from verticapy.datasets import load_titanic
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import verticapy.sql.functions as vpf
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titanic = load_titanic()
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titanic["has_title"] = vpf.regexp_like(titanic["name"], '([A-Za-z])+\\.')
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_like.html", "w")
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html_file.write(titanic[["name", "has_title"]]._repr_html_())
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html_file.close()
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titanic["new_title"] = vpf.regexp_replace(titanic["name"],
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'([A-Za-z])+\. ',
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'([A-Za-z])+\\.',
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'[title here] ')
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display(titanic[["name", "new_title"]])
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.. ipython:: python
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:suppress:
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:okwarning:
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from verticapy.datasets import load_titanic
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299304
titanic = load_titanic()
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titanic["new_title"] = vpf.regexp_replace(titanic["name"], '([A-Za-z])+\. ', '[title here] ')
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titanic["new_title"] = vpf.regexp_replace(titanic["name"], '([A-Za-z])+\\.', '[title here] ')
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_replace.html", "w")
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'([A-Za-z])+\. ')
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'([A-Za-z])+\\.')
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display(titanic[["name", "title"]])
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.. ipython:: python
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:suppress:
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from verticapy.datasets import load_titanic
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titanic = load_titanic()
362-
titanic["title"] = vpf.regexp_substr(titanic["name"], '([A-Za-z])+\. ')
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titanic["title"] = vpf.regexp_substr(titanic["name"], '([A-Za-z])+\\.')
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html_file = open("SPHINX_DIRECTORY/figures/sql_functions_regexp_regexp_substr.html", "w")
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html_file.write(titanic[["name", "title"]]._repr_html_())
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html_file.close()

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