は、私はあなたが必要だと思うset_index
stack
と:
df1 = df.set_index('timestamp').stack().rename_axis(('dates', 'cols')).reset_index(name='C')
print (df1)
dates cols C
0 2012-01-01 A 2
1 2012-01-01 B 8
2 2012-01-02 A 3
3 2012-01-02 B 9
4 2012-01-03 A 5
5 2012-01-03 B 1
またはmelt
が、値の順序が異なっている:
df1 = df.melt(id_vars='timestamp', var_name='cols', value_name='C')
#pandas bellow 0.20.1
#df1 = pd.melt(df, id_vars='timestamp', var_name='cols', value_name='C')
print (df1)
timestamp cols C
0 2012-01-01 A 2
1 2012-01-02 A 3
2 2012-01-03 A 5
3 2012-01-01 B 8
4 2012-01-02 B 9
5 2012-01-03 B 1
https://pandas.pydata.org/pandas-docs/stable /generated/pandas.melt.html – ayhan
私の解決策はうまくいきません。問題は何ですか? – jezrael