Pandas string to datetime
In this article, you will learn how to convert a string format to datetime format using Python Pandas. Pandas is a Python library that is basically used for Data Analysis.
In any programming language, datetime is a common datatype. Date and Time are often written in strings or any other format that we should convert into a single format. In data science time series project, it is common practice to convert strings to a datetime objects. Python pandas contains feature for working with date and time. Here, we have mentioned how to convert a dataframe column of strings to a datatime format using Python Pandas inbuilt function pd.to_datetime().
Syntax of pd.to_datetime()
pandas.to_datetime(arg, errors=’raise’, dayfirst=False, yearfirst=False,
utc=None, box=True, format=None, exact=True, unit=None,
infer_datetime_format=False, origin=’unix’, cache=False)- arg: An integer, string, float, list or dict object to convert into a DateTime object.
- dayfirst: Boolean value, True if the input contains the day first
- yearfirst: Boolean value, True if the input contains the year first.
- utc: Boolean value, Returns the UTC Datetime Index if True.
- format: the position of the day, month, and year in the date.
Pandas convert date string to datetime
In the given example, we have converted a string to a date format.
import pandas as pd
# input in mm.dd.yyyy format
date = ['06.10.2020']
# output in yyyy-mm-dd format
print(pd.to_datetime(date))Output of the above code -
(env) c:\python37\Scripts\projects>stringtotime.py
DatetimeIndex(['2020-06-10'], dtype='datetime64[ns]', freq=None)Pandas convert data and time string to datetime
In the given example, we have converted a date and time string to a datetime format.
import pandas as pd
# date (mm.dd.yyyy) and time (H:MM:SS)
date = ['11.02.2020 5:50:10 PM']
# output in yyyy-mm-dd HH:MM:SS
print(pd.to_datetime(date))(env) c:\python37\Scripts\projects>stringtotime.py
DatetimeIndex(['2020-11-02 17:50:10'], dtype='datetime64[ns]', freq=None)Convert Strings to Datetime in Pandas DataFrame
In the given example, we have mentioned step by step process to convert Pandas DataFrame column type from string to datetime format. Suppose, we have the following data that we want to convert strings to datetime in Pandas DataFrame -
| Name | DOB |
| Ankita | 20110413 |
| Somya | 20020113 |
| Tanya | 20050713 |
| Kanika | 20100113 |
Create the dataframe
Here, we have created a DataFrame from the above data -
import pandas as pd
values = {'Name': ['Ankita', 'Somya', 'Tanya', 'Kanika'],
'DOB': ['20110413', '20020113', '20050713', '20100113']
}
df = pd.DataFrame(values, columns = ['Name','DOB'])
print (df)
print (df.dtypes)(env) c:\python37\Scripts\projects>stringtotime.py
Name DOB
0 Ankita 20110413
1 Somya 20020113
2 Tanya 20050713
3 Kanika 20100113
Name object
DOB object
dtype: objectConvert the Strings to Datetime in the DataFrame
import pandas as pd
values = {'Name': ['Ankita', 'Somya', 'Tanya', 'Kanika'],
'DOB': ['20110413', '20020113', '20050713', '20100113']
}
df = pd.DataFrame(values, columns = ['Name','DOB'])
df['DOB'] = pd.to_datetime(df['DOB'], format='%Y%m%d')
print (df)
print (df.dtypes)Output of the above code -
(env) c:\python37\Scripts\projects>stringtotime.py
Name DOB
0 Ankita 2011-04-13
1 Somya 2002-01-13
2 Tanya 2005-07-13
3 Kanika 2010-01-13
Name object
DOB datetime64[ns]
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