How to remove duplicates in pandas?

To remove duplicates in a pandas DataFrame, you can use the `drop_duplicates()` method. This method returns a new DataFrame with duplicate rows removed, based on one or more colum…

How to drop columns in pandas?

To drop columns in a pandas DataFrame, you can use the `drop()` method. Here is an example: ``` import pandas as pd # Create a DataFrame df = pd.DataFrame({'col1': [1, 2, 3], …

How to reformat dates in pandas?

To reformat dates in a pandas DataFrame, you first need to convert them to the datetime format using `pd.to_datetime()`. Once the dates are in the datetime format, you can use the…

How to select specific columns in pandas?

To select specific columns in a pandas DataFrame, you can use either bracket indexing `[]` or the `.loc[]` and `.iloc[]` operators. Here are some examples: ``` import pandas as…

How to split columns in pandas?

To split columns in pandas, you can use the `str.split()` method. This method splits a string column into multiple columns based on a delimiter and returns a DataFrame with the ne…

How to normalize data in pandas?

To normalize data in pandas, you can use the `sklearn.preprocessing` module, which includes the `MinMaxScaler` class for feature scaling. This class normalizes each column of a Da…

How to remove HTML tags in pandas?

To remove HTML tags from a pandas DataFrame, you can use the `BeautifulSoup` library's `.get_text()` method to extract the plain text from the HTML tags. Here is an example of h…

How to remove URLs in pandas?

To remove URLs from a pandas DataFrame column, you can use regular expressions to match and replace URLs with an empty string. Here is an example of how to remove URLs from a pa…

How to remove words from a list in pandas?

To remove words from a list in pandas, you can use the Series.str.replace() method. For example, let's say you have a Pandas Series of strings containing the words you want to rem…

How to remove repeated characters in pandas?

To remove repeated characters in a Pandas Series of strings, you can use the Series.str.replace() method with a regular expression that uses backreferences. For example: ``` im…