pandas Getting started with pandas Descriptive statistics
Example
Descriptive statistics (mean, standard deviation, number of observations, minimum, maximum, and quartiles) of numerical columns can be calculated using the .describe() method, which returns a pandas dataframe of descriptive statistics.
In [1]: df = pd.DataFrame({'A': [1, 2, 1, 4, 3, 5, 2, 3, 4, 1],
'B': [12, 14, 11, 16, 18, 18, 22, 13, 21, 17],
'C': ['a', 'a', 'b', 'a', 'b', 'c', 'b', 'a', 'b', 'a']})
In [2]: df
Out[2]:
A B C
0 1 12 a
1 2 14 a
2 1 11 b
3 4 16 a
4 3 18 b
5 5 18 c
6 2 22 b
7 3 13 a
8 4 21 b
9 1 17 a
In [3]: df.describe()
Out[3]:
A B
count 10.000000 10.000000
mean 2.600000 16.200000
std 1.429841 3.705851
min 1.000000 11.000000
25% 1.250000 13.250000
50% 2.500000 16.500000
75% 3.750000 18.000000
max 5.000000 22.000000
Note that since C is not a numerical column, it is excluded from the output.
In [4]: df['C'].describe()
Out[4]:
count 10
unique 3
freq 5
Name: C, dtype: object
In this case the method summarizes categorical data by number of observations, number of unique elements, mode, and frequency of the mode.
