从熊猫的数据框中选择日期时间

Question

I'm cleaning up a messy excel file and am trying to select rows if a datetime field exists. This is the dataframe I have.

           Unnamed: 0          June              2020           Unnamed: 3           Town     Permit          
0           DATE              PERMIT #        OWNER/BUILDER     PERMIT ADDRESS       Center   Code
1      2020-06-02 00:00:00     17785          Joe W             341 Ameth Way        NaN       BF      
2      2020-06-02 00:00:00     17786          Deinise S         198 Cedar Cir        NaN       MR     
3      2020-06-02 00:00:00     17787          John S            49 Jasp Way          NaN       MR 

I'd like to create a conditional statement that will search the dataframe and if a datetime exists in a row, keep the row else drop it. I would also like to drop the headers. Desired result:

1      2020-06-02 00:00:00     17785          Joe W             341 Ameth Way        NaN       BF      
2      2020-06-02 00:00:00     17786          Deinise S         198 Cedar Cir        NaN       MR     
3      2020-06-02 00:00:00     17787          John S            49 Jasp Way          NaN       MR 

Answer 1

#Concat  Unnamed: and 0 into one column to make it complete datet_time
df['Unnamed:']=df['Unnamed:'].str.cat(df['0'], sep=' ')

#Coerce df['Unnamed:'] into datetime. That will make any non datetime into NaNs or NaTs
df['Unnamed:']=pd.to_datetime(df['Unnamed:'],errors='coerce')

#Drop any NaN
d`f.dropna(inplace=True)`

Answer 2

I didn't like the idea of having to base my data clean up off a column name, so instead I based it off an index.

# convert the first column to a datetime column, put NaT in non-date fields
df['Date'] = pd.to_datetime(df.iloc[:,0], errors='coerce')

# drop any rows that did not convert to a datetime
df = df.dropna(subset=['Date'])