下面有一个数据框
>df = pd.DataFrame({'A':['apple','orange','grape','pear','banana'], \
'B':['She likes apples', 'I hate oranges', 'This is a random sentence',\
'This one too', 'Bananas are yellow']})
>print(df)
A B
0 apple She likes apples
1 orange I hate oranges
2 grape This is a random sentence
3 pear This one too
4 banana Bananas are yellow
我正在尝试获取 B 列包含 A 列中的值的所有行。
预期结果:
A B
0 apple She likes apples
1 orange I hate oranges
4 banana Bananas are yellow
我只能使用
获取一行>df[df['B'].str.contains(df.iloc[0,0])]
A B
0 apple She likes apples
我怎样才能获取所有这些行？
最佳答案
使用DataFrame.apply将两个值都转换为较低值并测试包含 in 并按 boolean indexing 过滤:
df = df[df.apply(lambda x: x.A in x.B.lower(), axis=1)]
或者列表理解解决方案:
df = df[[a in b.lower() for a, b in zip(df.A, df.B)]]
print (df)
A B
0 apple She likes apples
1 orange I hate oranges
4 banana Bananas are yellow
关于python - 选择 Pandas 中的行，其中一列中的值是另一列中值的子字符串，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/59208708/