There are multiple ways to add a new Column to an Existing DataFrame in Pandas in Python: Creating a Sample Dataframe. By using Dataframe.insert () method. By using Dataframe.assign () method. Using Dictionary. Using List. Using .loc () Adding More than One columns in Existing Dataframe. Creating a Sample Dataframe.. Using insert() Alternatively, you can also use pandas.DataFrame.insert().This method is usually useful when you need to insert a new column in a specific position or index.. For example, to add colC to the end of the DataFrame:. df.insert(len(df.columns), 'colC', s.values) print(df) colA colB colC 0 True 1 a 1 False 2 b 2 False 3 c To insert colC in between colA and colB:

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Assign a Custom Value to a Column in Pandas. In order to create a new column where every value is the same value, this can be directly applied. For example, if we wanted to add a column for what show each record is from (Westworld), then we can simply write: df['Show'] = 'Westworld' print(df) This returns the following:. 1. Pandas DataFrame Add Column from Python List. The first, and probably the easiest way to add a column to Pandas DataFrame is by using Python lists. You can either set a new column to have a constant value, or you can specify the value for each row. We'll explore both in this section. Add Column to Pandas DataFrame With Default Value