Python | Pandas dataframe.median()
Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas dataframe.median()
function return the median of the values for the requested axis
If the method is applied on a pandas series object, then the method returns a scalar value which is the median value of all the observations in the dataframe. If the method is applied on a pandas dataframe object, then the method returns a pandas series object which contains the median of the values over the specified axis.
Syntax:DataFrame.median(axis=None, skipna=None, level=None, numeric_only=None, **kwargs)
Parameters :
axis : Align object with threshold along the given axis.
skipna : Exclude NA/null values when computing the result
level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series
numeric_only : Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
Returns : median : Series or DataFrame (if level specified)
Example #1: Use median()
function to find the median of all the observations over the index axis.
import pandas as pd
df = pd.DataFrame({ "A" :[ 12 , 4 , 5 , 44 , 1 ],
"B" :[ 5 , 2 , 54 , 3 , 2 ],
"C" :[ 20 , 16 , 7 , 3 , 8 ],
"D" :[ 14 , 3 , 17 , 2 , 6 ]})
df
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Lets use the dataframe.median()
function to find the median over the index axis
Output :
Example #2: Use median()
function on a dataframe which has Na
values. Also find the median over the column axis.
import pandas as pd
df = pd.DataFrame({ "A" :[ 12 , 4 , 5 , None , 1 ],
"B" :[ 7 , 2 , 54 , 3 , None ],
"C" :[ 20 , 16 , 11 , 3 , 8 ],
"D" :[ 14 , 3 , None , 2 , 6 ]})
df
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Lets implement the median function.
df.median(axis = 1 , skipna = True )
|
Output :
Last Updated :
24 Nov, 2018
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