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Pandas DataFrame.mean()The mean() function is used to return the mean of the values for the requested axis. If we apply this method on a Series object, then it returns a scalar value, which is the mean value of all the observations in the dataframe. If we apply this method on a DataFrame object, then it returns a Series object which contains mean of values over the specified axis. SyntaxDataFrame.mean(axis=None, skipna=None, level=None, numeric_only=None, **kwargs) Parameters
ReturnsIt returns the mean of the Series or DataFrame if the level is specified. Example
# importing pandas as pd
import pandas as pd
# Creating the dataframe
info = pd.DataFrame({"A":[8, 2, 7, 12, 6],
"B":[26, 19, 7, 5, 9],
"C":[10, 11, 15, 4, 3],
"D":[16, 24, 14, 22, 1]})
# Print the dataframe
info
# If axis = 0 is not specified, then
# by default method return the mean over
# the index axis
info.mean(axis = 0)
Output A 7.0 B 13.2 C 8.6 D 15.4 dtype: float64 Example2
# importing pandas as pd
import pandas as pd
# Creating the dataframe
info = pd.DataFrame({"A":[5, 2, 6, 4, None],
"B":[12, 19, None, 8, 21],
"C":[15, 26, 11, None, 3],
"D":[14, 17, 29, 16, 23]})
# while finding mean, it skip null values
info.mean(axis = 1, skipna = True)
Output 0 11.500000 1 16.000000 2 15.333333 3 9.333333 4 15.666667 dtype: float64
Next TopicDataFrame.melt()
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