How to Convert Column to Datetime in pandas : Only 3 Steps

Do you have a date column that is of string type? And do you want to convert this column to datetime type? Then this post is for you. Here I will show you various methods for converting a Column to Datatime using Pandas.

Steps to Convert Column to Datetime in pandas

Step1: Import the necessary libraries.

In our examples, We are using only pandas libraries. Let’s import them using the import statement.

import pandas as pd

Step 2: Create a Sample Dataframe

Before converting the column to datetime , you have to create a pandas dataframe with at least one column as a Date. That column must contain the date of the string type. Let’s create them.

Copy, paste, and execute the entire code to create dataframe.

data = {"Date":["12/11/2020","13/11/2020","14/11/2020","15/11/2020"],
"Open":[1,2,3,4],"Close":[5,6,7,8],"Volume":[100,200,300,400]}
df = pd.DataFrame(data=data)

You will get the output dataframe as follow.

If you will use the df.info() method then you will know the type of each column and also the number of rows in that column.

df.info

Output

You can see the “Date” column has 4 records.

Step 3: Use the various method to convert Column to Datetime in pandas

In this section, you will know the method to convert the “Date” column to Datetime in pandas. Let’s know about them.

Method 1: Using pandas.to_datetime()

Pandas have an inbuilt function that allows you to convert columns to DateTime. And it is pd.to_datetime().

Use the following lines of code to convert the column to datetime.

df["Date"] = pd.to_datetime(df["Date"]

If you again print out the df then the output will look like the same as the sample dataframe creation. But the type of the Date column is different.

df.info()

Method 2: Using the astype() method.

The second method to convert Column to Datetime in pandas is applying astype(“datetime64[ns]”). It changes the type of the  “Date” column to datetime.

Execute the following lines of code to change it.

df["Date"] = df["Date"].astype('datetime64[ns]')

Now if you will print out the info of this dataframe you will get the output as below.

Method 3: Applying the lambda function with apply() function.

The third method to Convert Columns to Datetime in pandas is applying the lambda function on each “Date” column value. It can be done using the apply() method. And at last, you have to pass the lambda function.

Run the lines of code below.

df["Date"] = df["Date"].apply(lambda d : pd.to_datetime(d))

Now if you print the info of the dataframe. Then you will see that the “Date” Column has converted from string to datetime.

Conclusion

These are the three methods that allow you to Convert Columns to Datetime in pandas. It’s your choice to use any of the three methods.  If in your dataset the “date” column is in datetime64 and want to convert it to datetime. Then read Numpy datetime64 to datetime and Vice-Versa implementation.

Hope you have liked this article. If you have any questions then you can contact us for more information.

Source:

pandas.Dataframe.apply() 

pandas.to_datetime()