Python

[Kvinalpha]

Import necessary libraries

import pandas as pd
import matplotlib.pyplot as plt

Step 1: Load the dataset

Replace 'your_dataset.csv' with your actual dataset file

df = pd.read_csv('your_dataset.csv')

Step 2: Data Exploration

Display the first few rows of the dataset

print("First 5 rows of the dataset:")
print(df.head())

Display basic statistics of the dataset

print("\nBasic statistics of the dataset:")
print(df.describe())

Step 3: Basic Data Analysis

Example analysis: Count the number of unique values in a specific column

unique_values = df['column_name'].nunique()
print(f"\nNumber of unique values in 'column_name': {unique_values}")

Step 4: Visualizations

Example: Plot a histogram of a numerical column

plt.figure(figsize=(10, 6))
plt.hist(df['numerical_column'], bins=30, edgecolor='k', alpha=0.7)
plt.title('Histogram of Numerical Column')
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.show()

Example: Plot a bar chart of categorical column counts

category_counts = df['categorical_column'].value_counts()
plt.figure(figsize=(10, 6))
category_counts.plot(kind='bar', color='skyblue')
plt.title('Bar Chart of Categorical Column')
plt.xlabel('Category')
plt.ylabel('Count')
plt.show()

Step 5: Findings and Observations

Print findings and observations based on your analysis

print("\nFindings and Observations:")
print("1. Example finding: Describe your observation here.")
print("2. Example finding: Describe another observation here.")