learning.DataBinner.DataBinner Class Reference

Static Public Member Functions
def	bin_col (df, col_name, num_bins, do_qtls=True)

Detailed Description

This class is all static methods. When the data in a column of a
dataframe are floats, we want to group those floats into bins and assign
an int to each bin. We refer to this process as binning. This class is
mainly just a wrapper for some pandas methods that do most of the heavy
lifting.

Member Function Documentation

def learning.DataBinner.DataBinner.bin_col (   df,   col_name,   num_bins,   do_qtls = True  )

static

Bins INPLACE the column called col_name in the dataframe df. By
inplace we mean that df is changed: its column col_name is replaced
by a binned version. The function returns bin_edges, a list of the
edges of the bins, and bin_to_mean, a dictionary mapping bin number
to the mean value of the points inside the bin. This is mainly a
wrapper for the Pandas functions cut() and qcut().

Parameters
----------
df : pandas.DataFrame
col_name : str
    name of the column that you wish to bin
num_bins : int
    number of bins
do_qtls : bool
    do quantiles. If True, will bin into quantiles, if False will
    use equal length bins.

Returns
-------
(list(float), list(float))

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The documentation for this class was generated from the following file:

• learning/DataBinner.py