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The day_name() function in pandas returns the day name of a given Timestamp object.

To extract the day of the week from a date type column in a Pandas DataFrame, we can use the dt accessor. The dt accessor provides access to several datetime properties and methods, including the day_name() method, which returns the name of the day of the week.

Example 1: Adding Days to Date in Pandas DataFrame Column Here, the DataFrame contains one column represented as a DateTime object using the ?pandas. to_datetime()? method. Next, the ?pandas. Timedelta()? method adds the days to the specified column of the Pandas DataFrame.

To find the day of the week from the pandas' Timestamp object, we use the attribute, . dayofweek . The Timestamp object is similar to the Python's datetime object.

The datetime module comes with a weekday() function, which returns the day of the week as an integer (where Monday is 0 and Sunday is 6). To use this function, you can call it on a date or datetime object. The current local date is 5/23/2023 and the weekday is Monday.

To access the datetime index using strings, we first need to ensure that the index is set to a datetime type. We can then use strings in the format YYYY-MM-DD to access specific dates or partial strings to access ranges of dates. With this knowledge, you can now efficiently work with time-series data in Pandas.

DatetimeIndex [source] Immutable ndarray of datetime64 data, represented internally as int64, and which can be boxed to Timestamp objects that are subclasses of datetime and carry metadata such as frequency information.

To convert the index to datetime, we can use the pd. to_datetime() function. This function takes a Series or list-like object and returns a new Series representing the datetime values. As we can see, the index is now of type datetime64[ns], which means it's in a datetime format.