pandas.DataFrame.drop — pandas 2.3.2 documentation

You can insert columns (or rows) or drop columns (or rows) in data frame.

Import the library:

import pandas as pd

Prepare the data frame

data = {
    "WorkerID": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
    "Age": [25, None, 35, 30, 24, 28, None, 32, 27, None],
    "Salary": [50000, 54000, None, 58000, 45000, 60000, 49000, None, None, 47000]
}

df = pd.DataFrame(data)
print("Original DataFrame:\\n", df)

Output:

Original DataFrame:
    WorkerID   Age   Salary
0         1  25.0  50000.0
1         2   NaN  54000.0
2         3  35.0      NaN
3         4  30.0  58000.0
4         5  24.0  45000.0
5         6  28.0  60000.0
6         7   NaN  49000.0
7         8  32.0      NaN
8         9  27.0      NaN
9        10   NaN  47000.0

You can insert a new column by simply specifying the columns with some values.

# Insert a new column
df["Department"] = ["HR", "Finance", "IT", "HR", "IT", "Finance", "IT", "HR", "Finance", "HR"]
print("DataFrame after inserting 'Department' column:\\n", df)

Output:

DataFrame after inserting 'Department' column:
    WorkerID   Age   Salary Department
0         1  25.0  50000.0         HR
1         2   NaN  54000.0    Finance
2         3  35.0      NaN         IT
3         4  30.0  58000.0         HR
4         5  24.0  45000.0         IT
5         6  28.0  60000.0    Finance
6         7   NaN  49000.0         IT
7         8  32.0      NaN         HR
8         9  27.0      NaN    Finance
9        10   NaN  47000.0         HR

You can also insert a new row to the data frame using df.loc().

# Insert a new row
df.loc[len(df)] = [11, 29, 55000, "HR"]
print("DataFrame after inserting new row:\\n", df)