Unable to combine date and time in pandas
0
I would like to combine the following date and time columns to 1 date_time column:
casinghourly[['Date','Time']].head()
Out[275]:
Date Time
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
I've used the following code:
casinghourly.loc[:,'Date_Time'] = pd.to_datetime(casinghourly.Date.astype(str)+' '+casinghourly.Time.astype(str))
But I get the following error:
ValueError: Unknown string format
Fyi:
casinghourly[['Date','Time']].dtypes
Out[276]:
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
Can somebody help me here please?
python pandas datetime
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
add a comment |
0
I would like to combine the following date and time columns to 1 date_time column:
casinghourly[['Date','Time']].head()
Out[275]:
Date Time
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
I've used the following code:
casinghourly.loc[:,'Date_Time'] = pd.to_datetime(casinghourly.Date.astype(str)+' '+casinghourly.Time.astype(str))
But I get the following error:
ValueError: Unknown string format
Fyi:
casinghourly[['Date','Time']].dtypes
Out[276]:
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
Can somebody help me here please?
python pandas datetime
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
add a comment |
0
0
0
I would like to combine the following date and time columns to 1 date_time column:
casinghourly[['Date','Time']].head()
Out[275]:
Date Time
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
I've used the following code:
casinghourly.loc[:,'Date_Time'] = pd.to_datetime(casinghourly.Date.astype(str)+' '+casinghourly.Time.astype(str))
But I get the following error:
ValueError: Unknown string format
Fyi:
casinghourly[['Date','Time']].dtypes
Out[276]:
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
Can somebody help me here please?
python pandas datetime
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
I would like to combine the following date and time columns to 1 date_time column:
casinghourly[['Date','Time']].head()
Out[275]:
Date Time
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
I've used the following code:
casinghourly.loc[:,'Date_Time'] = pd.to_datetime(casinghourly.Date.astype(str)+' '+casinghourly.Time.astype(str))
But I get the following error:
ValueError: Unknown string format
Fyi:
casinghourly[['Date','Time']].dtypes
Out[276]:
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
Can somebody help me here please?
python pandas datetime
python pandas datetime
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
asked Nov 16 '18 at 6:55
IndigoChildIndigoChild
340312
340312
add a comment |
add a comment |
1 Answer
1
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oldest
votes
2
You can directly concat datetime64[ns] with timedelta64[ns]:
df['Date'] = df['Date']+df['Time']
print(df['Date'])
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
Name: Date, dtype: datetime64[ns]
print(df)
Date Time
0 2014-01-01 00:00:00 00:00:00
1 2014-01-01 01:00:00 01:00:00
2 2014-01-01 02:00:00 02:00:00
3 2014-01-01 03:00:00 03:00:00
4 2014-01-01 04:00:00 04:00:00
print(df.dtypes)
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
2
You can directly concat datetime64[ns] with timedelta64[ns]:
df['Date'] = df['Date']+df['Time']
print(df['Date'])
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
Name: Date, dtype: datetime64[ns]
print(df)
Date Time
0 2014-01-01 00:00:00 00:00:00
1 2014-01-01 01:00:00 01:00:00
2 2014-01-01 02:00:00 02:00:00
3 2014-01-01 03:00:00 03:00:00
4 2014-01-01 04:00:00 04:00:00
print(df.dtypes)
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
add a comment |
2
You can directly concat datetime64[ns] with timedelta64[ns]:
df['Date'] = df['Date']+df['Time']
print(df['Date'])
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
Name: Date, dtype: datetime64[ns]
print(df)
Date Time
0 2014-01-01 00:00:00 00:00:00
1 2014-01-01 01:00:00 01:00:00
2 2014-01-01 02:00:00 02:00:00
3 2014-01-01 03:00:00 03:00:00
4 2014-01-01 04:00:00 04:00:00
print(df.dtypes)
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
add a comment |
2
2
2
You can directly concat datetime64[ns] with timedelta64[ns]:
df['Date'] = df['Date']+df['Time']
print(df['Date'])
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
Name: Date, dtype: datetime64[ns]
print(df)
Date Time
0 2014-01-01 00:00:00 00:00:00
1 2014-01-01 01:00:00 01:00:00
2 2014-01-01 02:00:00 02:00:00
3 2014-01-01 03:00:00 03:00:00
4 2014-01-01 04:00:00 04:00:00
print(df.dtypes)
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
You can directly concat datetime64[ns] with timedelta64[ns]:
df['Date'] = df['Date']+df['Time']
print(df['Date'])
0 2014-01-01 00:00:00
1 2014-01-01 01:00:00
2 2014-01-01 02:00:00
3 2014-01-01 03:00:00
4 2014-01-01 04:00:00
Name: Date, dtype: datetime64[ns]
print(df)
Date Time
0 2014-01-01 00:00:00 00:00:00
1 2014-01-01 01:00:00 01:00:00
2 2014-01-01 02:00:00 02:00:00
3 2014-01-01 03:00:00 03:00:00
4 2014-01-01 04:00:00 04:00:00
print(df.dtypes)
Date datetime64[ns]
Time timedelta64[ns]
dtype: object
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
answered Nov 16 '18 at 7:06
Sandeep KadapaSandeep Kadapa
7,398831
7,398831
add a comment |
add a comment |
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