Convert dates to pd.to_datetime where month could be either a number or month name

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You can use pd.to_datetime‘s format arg:

In [11]: s = pd.Series(["29062017", "01AUG2017"])

In [12]: pd.to_datetime(s, format="%d%m%Y", errors="coerce")
Out[12]:
0   2017-06-29
1          NaT
dtype: datetime64[ns]

In [13]: pd.to_datetime(s, format="%d%b%Y", errors="coerce")
Out[13]:
0          NaT
1   2017-08-01
dtype: datetime64[ns]

Note: the coerce argument means that failures will be NaT.

and fill in the NaNs from one into the other e.g. using fillna:

In [14]: pd.to_datetime(s, format="%d%m%Y", errors="coerce").fillna(
    ...:     pd.to_datetime(s, format="%d%b%Y", errors="coerce"))
Out[14]:
0   2017-06-29
1   2017-08-01
dtype: datetime64[ns]

Any strings that don’t match either format will remain NaT.

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