# 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 : 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 : df
Out:
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 : df.describe()
Out:
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 : df['C'].describe()
Out:
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. PDF - Download pandas for free