pandas.DataFrame.mean¶
Return the mean of the values for the requested axis.
- param axis
- {index (0), columns (1)}
Axis for the function to be applied on.
- param skipna
- bool, default True
Exclude NA/null values when computing the result.
- param level
- int or level name, default None
If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.
- param numeric_only
- bool, default None
Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series. **kwargs Additional keyword arguments to be passed to the function.
- return
Series or DataFrame (if level specified)
Limitations¶
Parameters axis
, level
and numeric_only
are unsupported.
Examples¶
import pandas as pd
import numpy as np
from numba import njit
@njit
def dataframe_mean():
df = pd.DataFrame({"A": [.2, .0, .6, .2],
"B": [2, 0, 6, 2],
"C": [-1, np.nan, 1, np.inf]})
return df.mean()
print(dataframe_mean())
$ python ./dataframe/dataframe_mean.py
A 0.25
B 2.50
C inf
dtype: float64
See also
- Series.mean
Return the mean of the values for the Series.