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By use + operator simply you can concatenate two or multiple text/string columns in pandas DataFrame. Note that when you apply + operator on numeric columns it actually does addition instead of concatenation.

How to append two DataFrames in Pandas? Create a two-dimensional, size-mutable, potentially heterogeneous tabular data, df1. Print the input DataFrame, df1. Create another DataFrame, df2, with the same column names and print it. Use the append method, df1. ... Print the resultatnt DataFrame.

In pandas you can add/append a new column to the existing DataFrame using DataFrame. insert() method, this method updates the existing DataFrame with a new column. DataFrame. assign() is also used to insert a new column however, this method returns a new Dataframe after adding a new column.

You can add/append a new column to the DataFrame based on the values of another column using df. assign() , df. apply() , and, np. where() functions and return a new Dataframe after adding a new column.

Another way to combine DataFrames is to use columns in each dataset that contain common values (a common unique identifier). Combining DataFrames using a common field is called ?joining?. The columns containing the common values are called ?join key(s)?.

Pandas dataframe.append() function is used to append rows of other dataframe to the end of the given dataframe, returning a new dataframe object. Columns not in the original dataframes are added as new columns and the new cells are populated with NaN value.

Adding a column using Pandas Series You can simply assign the values of your Series into the existing DataFrame to add a new column: series = pd. Series([40, 38, 32.5, 27, 30], index=[0, 1, 2, 3, 4]) data['science_score'] = series.