Computer Science 3 Marks Each

Indexing operator is used to refer to the square brackets following an object. The .loc and .iloc indexers also use the indexing operator to make selections. In this indexing operator to refer to df[].

You can iterate over the rows of the DataFrame by using for loop in combination with an iterrows() and iterritems() call on the DataFrame.

"' A python script to input the values of Principal, Rate, and Time and calculate SI and CI."'

Reindexing is used to confirm DataFrame to a new index with optional filling logic. It places NA/NaN in that location where the values are not present in the previous index. It returns a new object unless the new index is produced as equivalent to the current one, and the value of copy becomes False. It is used to change the index of the rows and columns of the DataFrame.

We can add any new column to an existing DataFrame. The below code demonstrates how to add any new column to an existing DataFrame:

Create an empty DataFrame:

The below code shows how to create an empty DataFrame in Pandas:

# importing the pandas library

import pandas as pd

info = pd.DataFrame()

print (info)

Output:

Empty DataFrame

Columns: []

Index: []

The key features of the panda's library are as follows:

• Memory Efficient

• Data Alignment

• Reshaping

• Merge and join

• Time Series

A DataFrame is a widely used data structure of pandas and works with a two-dimensional array with labeled axes (rows and columns). DataFrame is defined as a standard way to store data and has two different indexes, i.e., row index and column index.

It consists of the following properties:

• The columns can be heterogeneous types like int and bool.

• It is a dictionary of Series structure where both the rows and columns are indexed. It is denoted as "columns" in the case of columns and "index" in case of rows.