Reputation: 79
I have a dateframe with a column named "date" which contains date in format :year month date. Some of the months and dates are with zero value, meaning that these dates are not valid, so I need to replace data for these values with NaT (not a time". I tried the following :
df["date"] = df["date"].replace(0, np.nan), also tried: df["date"] = df["date"].replace({'0':np.nan, 0:np.nan}) also : df["date"] = df["date"].replace(['0', 0], np.nan)
But none of the above is working. still have data like : 1970 0 0 1970 1 0 etc...
Upvotes: 3
Views: 523
Reputation: 25259
Use pd.to_datetime
with option errors='coerce'
.
Sample series s
:
Out[31]:
0 1970 0 0
1 1970 1 1
2 1970 1 0
dtype: object
s_out = pd.to_datetime(s, errors='coerce')
In [33]: s_out
Out[33]:
0 NaT
1 1970-01-01
2 NaT
dtype: datetime64[ns]
Upvotes: 1