IPL Data Analysis using Pandas AI

Analyzing IPL 2023 auction data is important for understanding player purchases, team spending and auction trends. In this guide, we’ll use PandasAI an AI-powered data analysis tool to gain insights from the IPL 2024 Auction dataset. Pandas AI enhances traditional Pandas by integrating AI-driven insights making it easier to extract meaningful information from large datasets. Key benefits include:

Step-by-Step IPL Data Analysis Using PandasAI

Step 1: Prerequisites

Before starting ensure that pandasAI and openai libraries are installed. Run the following command in your command prompt:

!pip install -q pandasai openai pandas

Step 2: Import necessary libraries

Step 3: Initialize instance of OpenAI LLM and pass it's API key

Step 4: Importing the IPL 2023 Auction dataset using pandas

We are using the IPL 2023 Auction dataset here. You can download dataset from here.

Output:

Step 5: Drop the "Unnamed: 0" column from the above dataset

Output:

Step 6: Create SmartDataframe Object

Step 7: Data Analysis using PandasAI

Now let's begin our analysis:

Prompt 1:

Output:

['Sam Curran', 'Cameron Green', 'Ben Stokes']

Prompt 2:

Output:

Well, it looks like the cheapest buys this season were Glenn Phillips for Sunrisers Hyderabad,
Raj Angad Bawa and Rishi Dhawan for Punjab Kings, Dhruv Jurel and K.C Cariappa
for Rajasthan Royals and many more. The full list includes 163 players and their respective teams.

Prompt 3:

Output:

👁 Team wise Total cost-Geeksforgeeks

Prompt 4:

Output:

There were 108 bowlers who remained unsold in the auction.
Their base price ranged from 2 million to 20 million.

Prompt 5:

Output:

('Number of players remained unsold this season:', 338)

Prompt 6:

Output:

TYPE
ALL-ROUNDER 65
BOWLER 64
BATSMAN 35
WICKETKEEPER 21

The majority of unsold players were All-Rounders and Bowlers.

Prompt 7:

Output:

0 Shivam Mavi
1 Joshua Little
2 Kane Williamson
Name: Player's List, dtype: object

Prompt 8:

Output:

The total amount of money spent by all teams in the auction is $20,040,000.

Prompt 9:

Output:

Prompt 10:

Output:

Prompt 11:

Output:

Lucknow Super Giants

Prompt 12:

Output:

Based on the data provided, the univariate analysis shows that we have seven variables: Player's List, Base Price, TYPE, COST IN ₹ (CR.), Cost IN $ (000), 2022 Squad and Team. The data types for these variables are object, object, object, float64, float64 and object respectively.

Prompt 13:

Output:

Unfortunately, I was not able to answer your question. Please try again. If the problem persists try rephrasing your question.

For this input PandasAI seems to have failed as the complexity and ambiguity increased.