我想將列轉(zhuǎn)換為子列。假設(shè)數(shù)據(jù)是這樣的； Q1 Q2:Q21 Q2:Q22 Q2:Q23 Q3:Q31 Q3:Q320 yes green blue green bus car1 no red orange blue car bike2 yes green yellow black car walk3 yes yellow green brown bus walk4 no green green red car bus對(duì)列進(jìn)行整形后，我想擁有； Q1 Q2 Q3 Q1 Q21 Q22 Q23 Q31 Q320 yes green blue green bus car1 no red orange blue car bike2 yes green yellow black car walk3 yes yellow green brown bus walk4 no green green red car bus在這里，我嘗試過的；import pandas as pdsurvey = pd.read_csv('survey.csv')# first column namessurvey_cols = [col.split(':')[0] for col in survey.columns]# unique column namessurvey_ucols = []for e in survey_cols: if e not in survey_ucols: survey_ucols.append(e)# second column names, subcolumnssurvey_subcols = []for col in survey_ucols: survey_subcols.append([subcol.split(':')[-1] for subcol in survey.columns if col in subcol])# create new dftuples = list(zip(survey_ucols,survey_subcols))cols = pd.MultiIndex.from_tuples(tuples, names=['mainQ', 'subQ'])survey_new = pd.DataFrame(survey, columns=cols)提前致謝
1 回答
紅顏莎娜
TA貢獻(xiàn)1842條經(jīng)驗(yàn) 獲得超13個(gè)贊
您可以使用Index.to_series和創(chuàng)建輔助數(shù)據(jù)幀Series.str.split，因此可能向前填充每行的缺失值ffill，最后分配回MultiIndex.from_arrays：
df = survey.columns.to_series().str.split(':', expand=True).ffill(axis=1)
survey.columns = pd.MultiIndex.from_arrays([df[0].tolist(), df[1].tolist()])
#simplified
#survey.columns = [df[0].tolist(), df[1].tolist()]
print (survey)
Q1 Q2 Q3
Q1 Q21 Q22 Q23 Q31 Q32
0 yes green blue green bus car
1 no red orange blue car bike
2 yes green yellow black car walk
3 yes yellow green brown bus walk
4 no green green red car bus
詳情：
print (df)
0 1
Q1 Q1 Q1
Q2:Q21 Q2 Q21
Q2:Q22 Q2 Q22
Q2:Q23 Q2 Q23
Q3:Q31 Q3 Q31
Q3:Q32 Q3 Q32
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