[英]Comparing common strings in two pandas dataframe columns
I have a pandas data frame as follows: 我有一个pandas数据框如下:
coname1 coname2
Apple [Microsoft, Apple, Google]
Yahoo [American Express, Jet Blue]
Gap Inc [American Eagle, Walmart, Gap Inc]
I want to create a new column that flags whether the string in coname1 is contained in conames. 我想创建一个新列,标记coname1中的字符串是否包含在conames中。 So, from the above example, the dataframe would now be: 因此,从上面的示例中,数据帧现在将是:
coname1 coname2 isin
Apple [Microsoft, Apple, Google] True
Yahoo [American Express, Jet Blue] False
Gap Inc [American Eagle, Walmart, Gap Inc] True
set up frame: 设置框架:
df =pd.DataFrame({'coname1':['Apple','Yahoo','Gap Inc'],
'coname2':[['Microsoft', 'Apple', 'Google'],['American Express', 'Jet Blue'],
['American Eagle', 'Walmart', 'Gap Inc']]})
try this: 试试这个:
df['isin'] =df.apply(lambda row: row['coname1'] in row['coname2'],axis=1)
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