📊 Data Analysis with Python

A structured collection of Python notebooks covering data analysis fundamentals, exploratory data analysis (EDA), visualization, and preprocessing using industry-standard libraries on real-world datasets.

🛠️ Tech Stack

• NumPy
• Pandas
• Matplotlib
• Seaborn
• EDA

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🔢 NumPy

• 1D & 2D Arrays
• Various Array Operations
• Access and Modifying Elements

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🐼 Pandas

• Series & DataFrames
• Data Loading
• Filtering & Sorting
• GroupBy & Aggregation
• Merge & Join
• Missing Value Handling

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📈 Matplotlib

• Line Plot
• Bar Chart
• Histogram
• Scatter Plot
• Pie Chart
• Figure Customization

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🎨 Seaborn

• Count Plot
• Box Plot
• Violin Plot
• Pair Plot
• Heatmap
• Distribution Plot

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🔍 Exploratory Data Analysis (EDA)

• Data Inspection

• Data Cleaning

• Descriptive Statistics

• Univariate Analysis

• Bivariate Analysis

• Correlation Analysis

• Outlier Detection

• Insight Generation

• Datasets Cleaned

  1. Red Wine Quality
  2. Flight Price
  3. Google Playstore

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Run Code More Easily

python -m venv .venv
.venv\Scripts\activate
pip install -r requirements.txt

Additional info

• df.describe() + Shift + Tab: shows important info
• df.drop('Route', axis=1, inplace=True): axis(0:row, 1:col)