我想根据索引中的值创建一个列：如果索引以字母值开头而不是 'I0'，则返回“P”，否则返回“C”。尝试过：df['new_col'] = ['P' if (x[0].isalpha() and not x[0].startswith("I0")) else 'C' for x in df.index]但它返回以以下开头的行的“P” 'I0'： A B C new_colIndex I00001 1.325337 4.692308 1.615385 PI00002 1.614780 3.615385 0.769231 PI00003 1.141453 5.461538 2.000000 PI00004 0.918300 8.538462 2.769231 PI00005 1.189606 11.846154 2.692308 PI00006 0.941459 7.153846 2.153846 PI00007 0.466383 12.153846 9.384615 PI00008 0.308627 198.692308 23.461538 PI00011 0.537142 23.384615 6.846154 PI00012 1.217390 11.923077 1.230769 PI00013 1.052840 3.384615 2.000000 P...可重现的例子：df = pd.DataFrame({'A': {'I00001': 1.3253365856660808, 'I00002': 1.6147800817881086, 'I00003': 1.1414534979918203, 'I00004': 0.9183004454646491, 'I00005': 1.1896061362142527, 'I00006': 0.941459102789141, 'I00007': 0.46638312473267185, 'I00008': 0.3086270976042302, 'I00011': 0.5371419441302684, 'I00012': 1.2173904641254587, 'I00013': 1.052839529263679, 'I00014': 1.3587324409735149, 'I00015': 3.464101615137755, 'I00016': 1.1989578808281798, 'I00018': 0.2433560755649686, 'I00019': 0.5510000980337852, 'I00020': 3.464101615137755, 'I00022': 1.0454523047666737, 'I00023': 1.3850513878332371, 'I00024': 1.3314720972390754}, 'B': {'I00001': 4.6923076923076925, 'I00002': 3.6153846153846154, 'I00003': 5.461538461538462, 'I00004': 8.538461538461538, 'I00005': 11.846153846153847, 'I00006': 7.153846153846154, 'I00007': 12.153846153846153, 'I00008': 198.69230769230768, 'I00011': 23.384615384615383, 'I00012': 11.923076923076923, 'I00013': 3.3846153846153846, 'I00014': 1.0,)
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TA贡献1828条经验 获得超6个赞
非循环解决方案numpy.where：
df['new_col'] = np.where(df.index.str[0].str.isalpha() &
~df.index.str.startswith("I0"), 'P', 'C')
您的解决方案 -x[0]从中删除x[0].startswith("I0")- 它测试第一个值，如果不是I0，则始终是True：
df['new_col'] = ['P' if (x[0].isalpha() and not x.startswith("I0"))
else 'C' for x in df.index]
测试：
df = pd.DataFrame({'A': {'AA00001': 1.3253365856660808,
'I00002': 1.6147800817881086,
'IR0003': 1.1414534979918203,
'00004': 0.9183004454646491,
'**00005': 1.1896061362142527,
'I00007': 0.46638312473267185}}
)
df['new_col'] = np.where(df.index.str[0].str.isalpha() &
~df.index.str.startswith("I0"), 'P', 'C')
df['new_col1'] = ['P' if (x[0].isalpha() and not x.startswith("I0"))
else 'C' for x in df.index]
print (df)
A new_col new_col1
**00005 1.189606 C C
00004 0.918300 C C
AA00001 1.325337 P P
I00002 1.614780 C C
I00007 0.466383 C C
IR0003 1.141453 P P
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您正在检查x[0].startswith("I0")您的代码，这是不正确的尝试这个（检查x.startswith("I0")）
df['new_col'] = ['P' if (x[0].isalpha() and not x.startswith("I0")) else 'C' for x in df.index]添加回答
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