map()的主要任务用于映射公共列的两个Series值。要映射两个Series,第一个Series的最后一列应与第二个Series的索引列相同,并且值应唯一。
Series.map(arg, na_action=None)
它返回与调用者具有相同索引的PandasSeries。
链接:https://www.learnfk.comhttps://www.learnfk.com/pandas/pandas-series-map.html
来源:LearnFk无涯教程网
import pandas as pd import numpy as np a = pd.Series(['Java', 'C', 'C++', np.nan]) a.map({'Java': 'Core'})
输出
0 Core 1 NaN 2 NaN 3 NaN dtype: object
import pandas as pd import numpy as np a = pd.Series(['Java', 'C', 'C++', np.nan]) a.map({'Java': 'Core'}) a.map('I like {}'.format, na_action='ignore')
输出
0 I like Java 1 I like C 2 I like C++ 3 I like nan dtype: object
import pandas as pd import numpy as np a = pd.Series(['Java', 'C', 'C++', np.nan]) a.map({'Java': 'Core'}) a.map('I like {}'.format) a.map('I like {}'.format, na_action='ignore')
输出
0 I like Java 1 I like C 2 I like C++ 3 NaN dtype: object
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