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In the data analysis of python, the custom operation of batch data can be easily realized by using apply (), map () and applymap (). Its usage is summarized as follows.

Function usage apply () is used to manipulate data in DataFrame by row or column. Map () is used to operate on every data in Series. Applymap () is used to manipulate every data in DataFrame. Example apply ()

Apply () is used to manipulate data in DataFrame by row or column.

Import pandas as pddata = [[110,120,110], [130,120,130]] columns= ['Chinese', 'mathematics', 'English'] df = pd.DataFrame (data=data, columns=columns) print (df) print ("=") print (lambda x: x.sum (), axis=1))

Where axis=1 stands for line alignment. An axis of 0 indicates a column alignment.

Map ()

Map () is used to manipulate every data in the Series.

Import pandas as pds1 = pd.Series ([11, 22, 33, 44, 55]) print (S1) print ("=") print (s1.map (lambda x: str (x) applymap

Applymap () is used for every data operation on DataFrame.

Manipulate every piece of data in DataFrame.

Take keeping two decimal places for each piece of data as an example:

Import pandas as pddata = [[110,120,110], [130,120,130]] columns= ['Chinese', 'mathematics', 'English'] df = pd.DataFrame (data=data, columns=columns) print (df) print ("=") print (df.applymap (lambda x:'% .2f'% x))

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