CODEWITHSUNDEEP
pythonpandas
Incognito
Incognito

Reputation: 351

How do I find the source code for a method in Pandas?

The following is the GitHub link for Python's Pandas package.

https://github.com/pandas-dev/pandas

I would like to find the source code for a specific method (for instance, iterrows). What would be the file path for this?

Upvotes: 0

Views: 1784

Answers (2)

juanpa.arrivillaga
juanpa.arrivillaga

Reputation: 96172

Python, in general, is easily introspect-able. You can use the inspect module if you want to do this programatically. so for example:

In [8]: import pandas as pd

In [9]: import inspect

In [10]: pd.DataFrame.iterrows
Out[10]: <function pandas.core.frame.DataFrame.iterrows(self)>

In [11]: inspect.getsourcefile(pd.DataFrame.iterrows)
Out[11]: '/Users/juan/anaconda3/envs/py38/lib/python3.8/site-packages/pandas/core/frame.py'

So you can go to pandas/core/frame.py. Note, this won't always work if it is, say, a method written in C as an extension. But it should for Python source code. In fact, you can even get the source code lines using inspect.getsourcelines, which returns a tuple of lines, line_number:

In [12]: inspect.getsourcelines(pd.DataFrame.iterrows)
Out[12]:
(['    def iterrows(self):\n',
  '        """\n',
  '        Iterate over DataFrame rows as (index, Series) pairs.\n',
  '\n',
  '        Yields\n',
  '        ------\n',
  '        index : label or tuple of label\n',
  '            The index of the row. A tuple for a `MultiIndex`.\n',
  '        data : Series\n',
  '            The data of the row as a Series.\n',
  '\n',
  '        it : generator\n',
  '            A generator that iterates over the rows of the frame.\n',
  '\n',
  '        See Also\n',
  '        --------\n',
  '        itertuples : Iterate over DataFrame rows as namedtuples of the values.\n',
  '        items : Iterate over (column name, Series) pairs.\n',
  '\n',
  '        Notes\n',
  '        -----\n',
  '\n',
  '        1. Because ``iterrows`` returns a Series for each row,\n',
  '           it does **not** preserve dtypes across the rows (dtypes are\n',
  '           preserved across columns for DataFrames). For example,\n',
  '\n',
  "           >>> df = pd.DataFrame([[1, 1.5]], columns=['int', 'float'])\n",
  '           >>> row = next(df.iterrows())[1]\n',
  '           >>> row\n',
  '           int      1.0\n',
  '           float    1.5\n',
  '           Name: 0, dtype: float64\n',
  "           >>> print(row['int'].dtype)\n",
  '           float64\n',
  "           >>> print(df['int'].dtype)\n",
  '           int64\n',
  '\n',
  '           To preserve dtypes while iterating over the rows, it is better\n',
  '           to use :meth:`itertuples` which returns namedtuples of the values\n',
  '           and which is generally faster than ``iterrows``.\n',
  '\n',
  '        2. You should **never modify** something you are iterating over.\n',
  '           This is not guaranteed to work in all cases. Depending on the\n',
  '           data types, the iterator returns a copy and not a view, and writing\n',
  '           to it will have no effect.\n',
  '        """\n',
  '        columns = self.columns\n',
  '        klass = self._constructor_sliced\n',
  '        for k, v in zip(self.index, self.values):\n',
  '            s = klass(v, index=columns, name=k)\n',
  '            yield k, s\n'],
 860)

Generally, also, you can just print the function/method and look at the information in the string representation, and pretty much figure it out:

In [19]: pd.DataFrame.iterrows
Out[19]: <function pandas.core.frame.DataFrame.iterrows(self)>

So just from that you could see it is in pandas.core.frame.

Upvotes: 4

Oleg Ivanytskyi
Oleg Ivanytskyi

Reputation: 1081

This site and this one have a button with a link (source). I usually just google the method I need and add the word source

Upvotes: 3

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