Pandas Convert Date (Datetime) To String Format

We are given a column containing datetime values in a pandas DataFrame and our task is to convert these datetime objects into string format. This conversion is useful for visualizing data, exporting it to external applications, or performing string operations. For example, if we have this input:

a = {
'dt': pd.to_datetime(['2024-01-01', '2024-01-02', '2024-01-03']),
'x': [101, 201, 301],
'y': [909, 1809, 2709]
}

Then the output after conversion to strings might look like:

dt x y
0 01-01-2024 101 909
1 02-01-2024 201 1809
2 03-01-2024 301 2709

Using astype(str)

The astype(str) method converts the datetime column directly into strings. This approach is simple but does not allow formatting customization.

import pandas as pd
a = {
    'dt': pd.to_datetime(['2024-01-01', '2024-01-02', '2024-01-03']),
    'x': [101, 201, 301],
    'y': [909, 1809, 2709]
}
df = pd.DataFrame(a)
print(type(df['dt'][0]))
df['dt'] = df['dt'].astype(str)
print(type(df['dt'][0]))

<class 'pandas._libs.tslibs.timestamps.Timestamp'>
<type 'str'>

Explanation:

• astype(str) changes the entire column dt from datetime to string type.
• type() checks the datatype before and after conversion.

Using strftime()

The strftime() method formats each datetime value into a string based on the format you specify.

import pandas as pd
a = {
    'dt': pd.to_datetime(['2024-01-01', '2024-01-02', '2024-01-03']),
    'x': [101, 201, 301],
    'y': [909, 1809, 2709]
}
df = pd.DataFrame(a)
df['dt'] = df['dt'].dt.strftime('%d-%m-%Y')
print(df)
df.info()

Output:

         dt    x     y
0  01-01-2024  101   909
1  02-01-2024  201  1809
2  03-01-2024  301  2709
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 3 entries, 0 to 2
Data columns (total 3 columns):
 #   Column  Non-Null Count  Dtype 
---  ------  --------------  ----- 
 0   dt      3 non-null      object
 1   x       3 non-null      int64 
 2   y       3 non-null      int64 

Explanation:

• strftime('%d-%m-%Y') converts each date to a custom string format.
• The dt accessor is used to apply string formatting on datetime columns.

Using apply() with lambda

You can convert datetime to string using the apply() function with a lambda expression. This offers flexibility to apply custom logic during conversion.

import pandas as pd
a = {
    'dt': pd.to_datetime(['2024-01-01', '2024-01-02', '2024-01-03']),
    'x': [101, 201, 301],
    'y': [909, 1809, 2709]
}
df = pd.DataFrame(a)
df['dt'] = df['dt'].apply(lambda d: d.strftime('%B %d, %Y'))
print(df)

                 dt    x     y
0  January 01, 2024  101   909
1  January 02, 2024  201  1809
2  January 03, 2024  301  2709

Explanation:

• .apply(lambda d: d.strftime(...)) allows full customization of the date format.
• You can use any valid format inside strftime — e.g., full month name with %B.