What is insert() in Pandas?

What is insert() in Pandas?

The insert() function in Pandas is used to insert a new column or row into a dataframe at a specified location.

This is often used to add a new column or row of data to an existing dataframe, without modifying the existing data.

Insert a new column

Here's an example of using the insert() function in Pandas to insert a new column into a dataframe:

import pandas as pd

# create a sample dataframe
df = pd.DataFrame({"A": [1, 2, 3, 4, 5],
                   "B": [6, 7, 8, 9, 10]})

# insert a new column C at position 2
df.insert(loc=2, column="C", value=[11, 12, 13, 14, 15])

# display the result
print(df)

This will insert a new column named C into the dataframe at position 2 (i.e., after the A column and before the B column), and populate the new column with the values [11, 12, 13, 14, 15].

The output will be:

   A   B   C
0  1   6  11
1  2   7  12
2  3   8  13
3  4   9  14
4  5  10  15

Insert a new row

You can also use the insert() function to insert a new row into a dataframe.

For example:

# insert a new row at position 2
df.loc[2] = [16, 17, 18]

# display the result
print(df)

This will insert a new row at position 2 in the dataframe, and populate the new row with the values [16, 17, 18].

The output will be:

    A   B   C
0   1   6  11
1   2   7  12
2  16  17  18
3   4   9  14
4   5  10  15

Conclusion

The insert() function is useful for inserting new columns or rows into a dataframe at a specified position, without modifying the existing data.