df1 = pd.DataFrame({
'Year': ["1A", "2A", "3A", "4A", "5A"],
'Tval1' : [1, 9, 8, 1, 6],
'Tval2' : [34, 56, 67, 78, 89]
})
它看起来更像这样
我想更改它，使其看起来像这样，第二列移动到单独的行下方。
想法是从中获取数字Year列，然后设置新的列名称Year列并重塑DataFrame.stack http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.stack.html:
df1['Year'] = df1['Year'].str.extract('(\d+)')
df = df1.set_index('Year')
#add letters by length of columns, working for 1 to 26 columns A-Z
import string
df.columns = list(string.ascii_uppercase[:len(df.columns)])
#here working same like
#df.columns = ['A','B']
df = df.stack().reset_index(name='Val')
df['Year'] = df['Year'] + df.pop('level_1')
print (df)
Year Val
0 1A 1
1 1B 34
2 2A 9
3 2B 56
4 3A 8
5 3B 67
6 4A 1
7 4B 78
8 5A 6
9 5B 89
另一个想法是DataFrame.melt http://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.melt.html:
df = (df1.replace({'Year': {'A':''}}, regex=True)
.rename(columns={'Tval1':'A','Tval2':'B'})
.melt('Year'))
df['Year'] = df['Year'] + df.pop('variable')
print (df)
Year value
0 1A 1
1 2A 9
2 3A 8
3 4A 1
4 5A 6
5 1B 34
6 2B 56
7 3B 67
8 4B 78
9 5B 89
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