Pandas DataFrame Apply () function (2)

Previous Pandas DataFrame the Apply () function (1) says How to convert DataFrame by using the Apply function to get a new DataFrame.

This article describes another use of the dataframe apply () function to get a new pandas Series:

The function in apply () receives a row (column) of arguments, returns a value by calculating a row (column), and finally returns a series:

Shows the conversion of the columns of the dataframe into a number, which is then returned to a series:

Give me a chestnut:

ImportNumPy as NPImportPandas as Pddf=PD. DataFrame ({'a': [4, 5, 3, 1, 2],    'b': [20, 10, 40, 50, 30],    'C': [25, 20, 5, 15, 10]})

# Apply the Np.mean () function to the entire dataframe, take the average of each column, and return a series containing the average of each column Printdf.apply (Np.mean)#Results:A 3.0b30.0C15.0Dtype:float64

# Apply the Np.max () function to the entire dataframe, taking the maximum value of each column, and returning a series containing the maximum values for each column

Print

# results: a 5 dtype:int64

If you want to return a series that consists of the second largest number in each column:

def get_second_largest (SE):     = Se.sort_values (ascending=False)    return sorted_se.iloc[1]    def  Second_largest (DF):    return  df.apply (get_second_largest)    print( Second_largest (DF))

A     4b    +c    Dtype:int64

Pandas DataFrame Apply () function (2)