Pandas is a powerful tool which is used for data analysis and is built on top of the python library. The Pandas library enables users to create and manipulate dataframes (Tables of data) and time series effectively and efficiently. These dataframes can be used for training and testing machine learning models and Analyzing data.
Converting Index to Columns
By default, each row of the dataframe has an index value. The rows in the dataframe are assigned index values from 0 to the (number of rows – 1) in a sequentially order with each row having one index value. There are many ways to convert an index to a column in a pandas dataframe. Let’s create a dataframe.
Method 1: The simplest method is to create a new column and pass the indexes of each row into that column by using the Dataframe.index function.
Method 2: We can also use the Dataframe.reset_index function to convert the index as a column. The inplace parameter reflects the change in the dataframe to stay permanent.
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- Pandas Dataframe.to_numpy() - Convert dataframe to Numpy array
- Convert a column to row name/index in Pandas
- Get the index of minimum value in DataFrame column
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- How to get column names in Pandas dataframe
- Capitalize first letter of a column in Pandas dataframe
- Python | Change column names and row indexes in Pandas DataFrame
- Apply uppercase to a column in Pandas dataframe
- How to lowercase column names in Pandas dataframe
- Get unique values from a column in Pandas DataFrame
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