I want to add two df columns df['Date'] and df['hour'] to create the column timestamp

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The problem is the hour column and the date column are like this:

Is there any way to add them to get a column starting with 2019-07-01 7:00:00 and so on


You can do:

df['datetime'] = pd.to_datetime(df['Date']) + pd.to_timedelta('1H') * df['Hour']

# or
# df['datetime'] = pd.to_datetime(df['Date']) + pd.to_timedelta(df['Hour'], unit='H')

How to sum two columns in a pandas DataFrame in Python, Select each column of DataFrame df through the syntax df["column_name"] and add them together to get a pandas Series containing the sum of each row. Create a new column in the DataFrame through the syntax df["new_column"] and set it equal to this Series to add it to the DataFrame. Case 2: Add Multiple Columns to Pandas DataFrame. What if you want to add multiple columns to your DataFrame? If that’s the case, simply separate those columns using a comma. For example, let’s say that you want to add two columns to your DataFrame: The ‘Price’ column; and; The ‘Discount’ column


df['datetime'] = df[['Date', 'hour']].apply(lambda x: ' '.join(x), axis=1)

then:

df['datetime']= pd.to_datetime(df['datetime'])


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You can try something like this

df.apply(lambda t : pd.datetime.combine(t['date_column_name'],t['time_column_name']),1)

If both columns are string you can simply concatenate it as well

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Add New Column to Pandas DataFrame using Assign, Case 2: Add Multiple Columns to Pandas DataFrame. What if you want to add multiple columns to your DataFrame? If that's the case, simply separate those� In the second adding new columns example, we assigned two new columns to our dataframe by adding two arguments to the assign method. These two arguments will become the new column names. Furthermore, each of our new columns also has the two lists we used in the previous example added. This way the result is exactly the same as in the first example.


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