You can also compute the values in the Data Frame using df.sum(), df.mean(), df.median(), df.mode() and more.

pandas.DataFrame.median — pandas 2.3.2 documentation

Import the library:

import pandas as pd

The following dataset is given

data = {
    "WorkerID": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
    "Age": [25, 35, 35, 30, 24, 28, 28, 32, 27, 28],
    "Salary": [50000, 54000, 40000, 58000, 45000, 60000, 49000, 52000, 50000, 47000]
}

Create the data frame:

df = pd.DataFrame(data)
print(df)

Output:

   WorkerID  Age  Salary
0         1   25   50000
1         2   35   54000
2         3   35   40000
3         4   30   58000
4         5   24   45000
5         6   28   60000
6         7   28   49000
7         8   32   52000
8         9   27   50000
9        10   28   47000

• Return the shape of the dataset

df = pd.DataFrame(data)
# Shape of the dataset
row, column = df.shape
print("Rows:", row)
print("Columns:", column)

Output:

Rows: 10 
Columns: 3