Pandas: compute the mean of a column grouped by another column

FaCoffee Published at Dev

FaCoffee

Say I have a dataframe like this:

            gender     height      weight  C
2000-01-01    male  42.849980  157.500553  1
2000-01-02    male  49.607315  177.340407  1
2000-01-03    male  56.293531  171.524640  1
2000-01-04  female  48.421077  144.251986  2
2000-01-05    male  46.556882  152.526206  2
2000-01-06  female  68.448851  168.272968  1
2000-01-07    male  70.757698  136.431469  2
2000-01-08  female  58.909500  176.499753  3
2000-01-09  female  76.435631  174.094104  3
2000-01-10    male  45.306120  177.540920  2

How could I compute the mean of the height column, grouped by column C? This would yield 3 different values: the mean of those heights with C=1, that of those with C=2, and so forth.

So far I tried this but to no avail:

df['height'].mean(groupby='C')

-> returns TypeError: mean() got an unexpected keyword argument 'groupby'

EdChum

Your syntax is incorrect, there is no groupby arg for mean, you want to groupby on the col of interest and then call mean on the column of interest:

In [11]:
df.groupby('C')['height'].mean()

Out[11]:
C
1    54.299919
2    52.760444
3    67.672566
Name: height, dtype: float64

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edited at2021-04-13

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