Beginner Machine Learning | Pandas Python Library | Exercise: Indexing, Selecting, & Assigning

📊 "Kaggle Pandas Exercise: Indexing, Selecting, & Assigning - Data Wrangling Mastery!" 📊

🔍 We're tackling the Kaggle Pandas exercise on Indexing, Selecting, and Assigning. Let's put our data selection skills to the test!

📌 Setting Up the Environment:

import pandas as pd: Importing the Pandas library.

📊 Exercise 1: Selecting the "description" Column:

We'll select the "description" column and assign it to the variable desc.
We'll determine the type of desc (Pandas Series).

✏️ Exercise 2: Selecting the First Value:

We'll select the first value from the "description" column and assign it to first_description.

🌍 Exercise 3: Selecting the First Row:

We'll select the first row of the DataFrame and assign it to first_row.

📈 Exercise 4: Selecting the First 10 Values:

We'll select the first 10 values from the "description" column and assign it to first_descriptions.

🤖 Exercise 5: Selecting Specific Records:

We'll select records with index labels 1, 2, 3, 5, and 8 and assign them to sample_reviews.

🔥 Exercise 6: Selecting Specific Columns and Rows:

We'll create a DataFrame df with "country," "province," "region_1," and "region_2" columns for rows 0, 1, 10, and 100.

🧠 Exercise 7: Selecting Country and Variety:

We'll create a DataFrame df with "country" and "variety" columns for the first 100 records.

🚀 Exercise 8: Italian Wines DataFrame:

We'll create a DataFrame italian_wines containing reviews of wines made in Italy.

🔗 Exercise 9: Top Ocean Wines DataFrame:

We'll create a DataFrame top_ocean_wines with reviews of wines from Australia or New Zealand with at least 95 points.

🏁 Moving Forward:

We've successfully completed the "Indexing, Selecting, and Assigning" exercise.
We're now moving on to "Summary Functions and Maps."
Let's continue our Pandas journey!

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