如何从列名中获取字符串并在 python 中熔化多个列?
How to get a string from column names and melt multiple columns in python?
我有这个 table 我需要把这个 table 融化成像预期的 table 我需要从中获取点名称(a 和 b)列名称并让 bq 和进度列融化。
type bq a bq b progress a progress b
P 1 1 1 2
Q 2 3 4 2
R 2 1 1 2
预期结果如下:
type point bq progress
P a 1 1
P b 1 2
Q a 2 4
Q b 3 2
R a 2 1
R b 1 2
如何在python中做到?
试试这个:
df = pd.DataFrame({'type':['p','q','r'],
'bq a':['1','2','2'],
'bq b':['1','3','1'],
'progress a':['1','4','1'],
'progress b':['2','2','2']})
df_bq = pd.melt(df, id_vars =['type'], value_vars =['bq a','bq b'])
df_bq.columns = ['type','point','bq']
df_bq['point'] = df_bq['point'].apply(lambda x:x.replace('bq ',''))
df_bq.sort_values(by = 'point')
df_p = pd.melt(df, id_vars =['type'], value_vars =['progress a','progress b'])
df_p.columns = ['type','point','progress']
df_p['point'] = df_p['point'].apply(lambda x:x.replace('progress ',''))
df_p.sort_values(by = 'point')
df_concat = pd.concat([df_bq, df_p['progress']], axis=1)
df_concat
结果:
我有这个 table 我需要把这个 table 融化成像预期的 table 我需要从中获取点名称(a 和 b)列名称并让 bq 和进度列融化。
type bq a bq b progress a progress b
P 1 1 1 2
Q 2 3 4 2
R 2 1 1 2
预期结果如下:
type point bq progress
P a 1 1
P b 1 2
Q a 2 4
Q b 3 2
R a 2 1
R b 1 2
如何在python中做到?
试试这个:
df = pd.DataFrame({'type':['p','q','r'],
'bq a':['1','2','2'],
'bq b':['1','3','1'],
'progress a':['1','4','1'],
'progress b':['2','2','2']})
df_bq = pd.melt(df, id_vars =['type'], value_vars =['bq a','bq b'])
df_bq.columns = ['type','point','bq']
df_bq['point'] = df_bq['point'].apply(lambda x:x.replace('bq ',''))
df_bq.sort_values(by = 'point')
df_p = pd.melt(df, id_vars =['type'], value_vars =['progress a','progress b'])
df_p.columns = ['type','point','progress']
df_p['point'] = df_p['point'].apply(lambda x:x.replace('progress ',''))
df_p.sort_values(by = 'point')
df_concat = pd.concat([df_bq, df_p['progress']], axis=1)
df_concat
结果: