We can convert DateTime to Date in pandas by using pandas.Series.dt.date and dt.normalize() methods. In Pandas, DateTime is a collection of dates and times in the format of “YYYY-MM-DD HH:MM:SS” where YYYY-MM-DD is referred to as the date and HH:MM:SS is referred to as Time.
In this article, I will explain convert DateTime to date by extracting only date from the date and time column of DataFrame.
Key Points -
- Converting datetime to date in Pandas is often useful to simplify data or match formats in date-only datasets.
- By default, datetime columns include both date and time components. Converting to date removes the time component.
- Use the
.dt.dateaccessor to extract the date from a datetime column. - After extraction, assign the result back to the original column or to a new column as needed.
- Ensure the column is in datetime format first, using
pd.to_datetime()if necessary. - For DataFrames with a datetime index, use
.index.dateto access just the date portion of each index entry.
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Quick Examples of Pandas Convert Datetime to Date
Below are some quick examples of converting the DateTime column to Date.
# Quick examples of convert Datetime to Date
# Example 1: Using date function
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.date
# Example 2: Using single date function
Datetime = '2021-11-15 21:04:15'
df2 = pd.to_datetime(Datetime).date()
# Example 3: Using normalize() method
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.normalize()
To run some examples of converting DateTime to Date in pandas, let’s create a Pandas DataFrame.
# Create Pandas DataFrame
import pandas as pd
technologies = ({
'Courses':["Spark","PySpark","Hadoop","Python","Pandas"],
'Fee':[22000,25000,23000,24000,26000],
"InsertedDateTime":['2021-11-15 21:04:15','2020-05-04 22:04:10','2018-01-26 15:23:14','2019-02-18 10:05:18','2021-12-10 15:13:21']
})
df = pd.DataFrame(technologies)
print("Create DataFrame:\n", df)
Yields below output.
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Convert Datetime to Date
The Datetime column can store the date and time together, If you want just the date and do not want time in format YYYY-MM-DD format use pandas.Series.dt.date. Here, pandas.to_datetime() is used to convert the String column to DateTime.
# Using Date function
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.date
print("After converting datetime to date:\n", df)
Yields below output.
If the date in the string column is already in date format, then just use date() to truncate the time.
# Using single date function to get
# date from datetime column
Datetime = '2021-11-15 21:04:15'
df2 = pd.to_datetime(Datetime).date()
print(df2)
# Output:
# 2021-11-15
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Convert Datetime to Date Using normalize() Method
You can convert DateTime to date using the normalize() method. Use pd.to_datetime(df["InsertedDateTime"]).dt.normalize() method to normalize the data by extracting the date from DateTime.
# Using normalize() method
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.normalize()
print("After converting datetime to date:\n", df)
Yields below output.
# Output:
# After converting datetime to date:
Courses Fee InsertedDateTime Date
0 Spark 22000 2021-11-15 21:04:15 2021-11-15
1 PySpark 25000 2020-05-04 22:04:10 2020-05-04
2 Hadoop 23000 2018-01-26 15:23:14 2018-01-26
3 Python 24000 2019-02-18 10:05:18 2019-02-18
4 Pandas 26000 2021-12-10 15:13:21 2021-12-10
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Complete Example Of Convert Datetime to Date
# Example Of Convert Datetime to Date
import pandas as pd
technologies = ({
'Courses':["Spark","PySpark","Hadoop","Python","Pandas"],
'Fee':[22000,25000,23000,24000,26000],
"InsertedDateTime":['2021-11-15 21:04:15','2020-05-04 22:04:10','2018-01-26 15:23:14','2019-02-18 10:05:18','2021-12-10 15:13:21']
})
df = pd.DataFrame(technologies)
print(df)
# Using Date function
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.date
print(df)
# Using single date function
Datetime = '2021-11-15 21:04:15'
df2 = pd.to_datetime(Datetime).date()
print(df2)
# Using normalize() method
df['Date'] = pd.to_datetime(df["InsertedDateTime"]).dt.normalize()
print(df)
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Frequently Asked Questions on Convert Datetime to Date
If you have a column of datetime objects in a Pandas DataFrame and you want to convert it to date objects, you can use the dt.date accessor. For example, df['datetime_column'].dt.date is used to extract the date portion of the datetime objects in the 'datetime_column', and a new column 'date_column' is created to store the date objects.
To convert a datetime column to a date column in a Pandas DataFrame, you can use the dt accessor along with the date attribute. For example, the pd.to_datetime function is used to convert the 'datetime_column' to a datetime data type. Then, the dt.date attribute is used to extract the date part and create a new 'date_column'. Adjust the column names based on your actual DataFrame.
To set the date column as the index of the DataFrame in Pandas, you can use the set_index method. For example, the set_index method is used to set the 'date_column' as the index of the DataFrame. The inplace=True parameter modifies the DataFrame in place without the need to create a new variable.
You can convert a datetime column to a date without creating a new column by directly overwriting the existing datetime column. For example, the original 'datetime_column' is directly overwritten with the date values using df['datetime_column'] = df['datetime_column'].dt.date. This modifies the DataFrame in place, and the 'datetime_column' now contains date values.
If your datetime column has a different format, you may need to specify the format when using the pd.to_datetime function. For example, the format parameter in pd.to_datetime is used to specify the format of the datetime strings in the 'datetime_column'. Adjust the format string ('%d-%b-%Y %H:%M:%S' in this case) based on the actual format of your datetime column.
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Conclusion
In this article, I have explained convert DateTime to date in pandas by using pandas.Series.dt.date and dt.normalize(), and date() function and with several examples.
Happy Learning !!
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