Convert String to Date - ( Pandas Time Series )

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Syntax

pd.to_datetime(arg, format=None, errors='raise', utc=None, box=True, infer_datetime_format=False)

Example

import pandas as pd

date_string = "2021-09-30"
date_object = pd.to_datetime(date_string)

print(date_object)

Output

2021-09-30 00:00:00

Explanation

pd.to_datetime() is a function provided by the Pandas library in Python for converting a string to a datetime object. It is useful when dealing with time series data, where dates and times are often represented as strings.

In the above example, we pass a date string "2021-09-30" as an argument to pd.to_datetime(). The function returns a datetime object representing the date and time. By default, the function assumes that the date string is in the format "YYYY-MM-DD", but you can specify a custom format using the format parameter.

Use

pd.to_datetime() is useful for transforming date strings into datetime objects, which can be used for time series analysis. The function can be used to process large amounts of data efficiently and accurately.

Important Points

• pd.to_datetime() is a function provided by the Pandas library for converting a string to a datetime object
• The function assumes that the date string is in the format "YYYY-MM-DD" by default, but a custom format can be specified using the format parameter
• The function is useful for processing large amounts of time series data efficiently and accurately

Summary

In conclusion, pd.to_datetime() is a useful function provided by the Pandas library for converting a string to a datetime object. It is widely used in time series analysis and can be used to process large amounts of data efficiently and accurately. The function is flexible and can be customized to process date strings in different formats.