パンダ：「年月」形式の列（期間）はどのように生成できますか？私が試した何

Question

は

In [20]: df.head() 
Out[20]: 
    year month  capital  sales  income  profit   debt 
0 2000  6 -19250379.0 37924704.0 -4348337.0 2571738.0 192842551.0 
1 2000  12 -68357153.0 27870187.0 -49074146.0 -20764204.0 190848380.0 
2 2001  6 -65048960.0 30529435.0 -1172803.0 2000427.0 197383572.0 
3 2001  12 -90129943.0 17135480.0 -24208501.0 -1012230.0 191464941.0 
4 2002  6 14671980.0 31377347.0 2188125.0 3660938.0 101355088.0 

た：

df['date'] = pd.to_datetime(df['year']*10000 + df['month']*100, format="%Y%m")

が、それはエラーが発生しました：私は 'その日' は逃しているためであると考え

In [21]: df['date'] = pd.to_datetime(df['year']*10000 + df['month']*100, format="%Y%m" 
    ...:) 
--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-21-31bfca8c5941> in <module>() 
----> 1 df['date'] = pd.to_datetime(df['year']*10000 + df['month']*100, format="%Y%m") 

~/.pyenv/versions/3.6.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin) 
    507  elif isinstance(arg, ABCSeries): 
    508   from pandas import Series 
--> 509   values = _convert_listlike(arg._values, False, format) 
    510   result = Series(values, index=arg.index, name=arg.name) 
    511  elif isinstance(arg, (ABCDataFrame, MutableMapping)): 

~/.pyenv/versions/3.6.0/lib/python3.6/site-packages/pandas/core/tools/datetimes.py in _convert_listlike(arg, box, format, name, tz) 
    412      try: 
    413       result = tslib.array_strptime(arg, format, exact=exact, 
--> 414              errors=errors) 
    415      except tslib.OutOfBoundsDatetime: 
    416       if errors == 'raise': 

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_strptime (pandas/_libs/tslib.c:63753)() 

TypeError: 'int' object is unsliceable 

を。

どうすればいいですか？

Answer 1

In [223]: df['date'] = pd.to_datetime(df[['year','month']].assign(day=1)).dt.to_period('M') 

In [224]: df 
Out[224]: 
    year month  capital  sales  income  profit   debt date 
0 2000  6 -19250379.0 37924704.0 -4348337.0 2571738.0 192842551.0 2000-06 
1 2000  12 -68357153.0 27870187.0 -49074146.0 -20764204.0 190848380.0 2000-12 
2 2001  6 -65048960.0 30529435.0 -1172803.0 2000427.0 197383572.0 2001-06 
3 2001  12 -90129943.0 17135480.0 -24208501.0 -1012230.0 191464941.0 2001-12 
4 2002  6 14671980.0 31377347.0 2188125.0 3660938.0 101355088.0 2002-06 

又は

In [208]: df['date'] = pd.PeriodIndex(pd.to_datetime(df[['year','month']].assign(day=1)), 
             freq='M') 

In [209]: df 
Out[209]: 
    year month  capital  sales  income  profit   debt date 
0 2000  6 -19250379.0 37924704.0 -4348337.0 2571738.0 192842551.0 2000-06 
1 2000  12 -68357153.0 27870187.0 -49074146.0 -20764204.0 190848380.0 2000-12 
2 2001  6 -65048960.0 30529435.0 -1172803.0 2000427.0 197383572.0 2001-06 
3 2001  12 -90129943.0 17135480.0 -24208501.0 -1012230.0 191464941.0 2001-12 
4 2002  6 14671980.0 31377347.0 2188125.0 3660938.0 101355088.0 2002-06