To convert strings to datetime objects in Python using pandas, you can use the to_datetime()
function. Here’s an example:
import pandas as pd
# Example data with string dates
data = {'date': ['2022-01-01', '2022-02-01', '2022-03-01']}
df = pd.DataFrame(data)
# Convert string dates to datetime objects
df['date'] = pd.to_datetime(df['date'])
print(df)
In this example, we have a DataFrame df
with a column named ‘date’ containing string dates. We use the pd.to_datetime()
function to convert the string dates to datetime objects. The resulting datetime objects are assigned back to the ‘date’ column of the DataFrame.
The pd.to_datetime()
function automatically parses the string dates and converts them to datetime objects. It can handle various date formats, such as ‘YYYY-MM-DD’, ‘MM/DD/YYYY’, and more.
After the conversion, you can perform various operations on the datetime column, such as sorting, filtering, extracting specific date components, and so on, using the functionality provided by pandas for datetime objects.
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