Pandas DataFrame mean() Method
Example
Return the average (mean) value for each column:
import pandas as pd
data = [[1, 1, 2], [6, 4, 2], [4, 2, 1], [4, 2,
3]]
df = pd.DataFrame(data)
print(df.mean())
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Definition and Usage
The mean() method returns a Series with the
mean value of each column.
Mean, Median, and Mode:
- Mean - The average value
- Median - The mid point value
- Mode - The most common value
By specifying the column axis (axis='columns'), the
mean()
method searches column-wise and returns the mean value for each row.
Syntax
dataframe.mean(axis, skipna, level, numeric_only, kwargs)
Parameters
The axis,
skipna, level, numeric_only
parameters are
keyword arguments.
| Parameter | Value | Description |
|---|---|---|
| axis | 0 |
Optional, Which axis to check, default 0. |
| skip_na | True |
Optional, default True. Set to False if the result should NOT skip NULL values |
| level | Number level name |
Optional, default None. Specifies which level ( in a hierarchical multi index) to check along |
| numeric_only | None |
Optional. Specify whether to only check numeric values. Default None |
| kwargs | Optional, keyword arguments. These arguments has no effect, but could be accepted by a NumPy function |
Return Value
A Series with the mean values.
If the level argument is specified, this method will return a DataFrame object.
This function does NOT make changes to the original DataFrame object.
