Data Analytics with Python

What you will learn

• Load, clean and reshape real datasets
• Summarise and chart data with pandas and Matplotlib
• Query databases with SQL
• Test whether a difference is real

Syllabus

137 lessons in 10 sections. Take them in order, or open any lesson directly.

1. Phase 1: Environment and Setup6 lessons

   1. Anaconda Distribution Setup3 min, 3 exercises
   2. Jupyter Notebook Interface3 min, 3 exercises
   3. Jupyter Shortcuts & Magic Commands3 min, 3 exercises
   4. Google Colab Walkthrough3 min, 3 exercises
   5. Virtual Environments for Data Science3 min, 3 exercises
   6. Installing Data Science Libraries (pip & conda)3 min, 3 exercises
2. Phase 2: Numerical Computing NumPy15 lessons

   1. Introduction to NumPy2 min, 3 exercises
   2. NumPy Array Creation1 min, 3 exercises
   3. NumPy Data Types (dtypes)1 min, 3 exercises
   4. Indexing and Slicing Arrays1 min, 3 exercises
   5. Shape Manipulation & Reshape1 min, 3 exercises
   6. Broadcasting in NumPy2 min, 3 exercises
   7. NumPy Arithmetic Operations1 min, 3 exercises
   8. NumPy Universal Functions (ufuncs)1 min, 3 exercises
   9. Staking and Splitting Arrays3 min, 3 exercises
   10. NumPy Random Module1 min, 3 exercises
   11. Linear Algebra with NumPy1 min, 3 exercises
   12. Statistical Functions in NumPy1 min, 3 exercises
   13. Saving and Loading NumPy Data1 min, 3 exercises
   14. Conditional Logic, Sorting & Set Logic4 min, 3 exercises
   15. Structured Arrays & Random Walks4 min, 3 exercises
3. Phase 3: Data Manipulation with Pandas26 lessons

   1. Introduction to Pandas2 min, 3 exercises
   2. Series and DataFrames1 min, 3 exercises
   3. Data Inspection (head, tail, info, describe)1 min, 3 exercises
   4. Indexing and Selecting Data (loc, iloc)2 min, 3 exercises
   5. Reindexing and Data Alignment2 min, 3 exercises
   6. Filtering with Conditions (and, or, isin, query)2 min, 3 exercises
   7. Sorting and Ranking2 min, 3 exercises
   8. Applying Functions (apply, map, applymap)1 min, 3 exercises
   9. Handling Missing Data (isna, fillna, dropna)1 min, 3 exercises
   10. Cleaning Data (astype, duplicates, string cleaning)1 min, 3 exercises
   11. Text and String Methods (str accessor and regex)2 min, 3 exercises
   12. Reading and Writing Data (CSV, Excel, JSON)1 min, 3 exercises
   13. Binary Formats and Web APIs (Parquet, pickle, requests)3 min, 3 exercises
   14. Correlation and Covariance2 min, 3 exercises
   15. Grouping and Aggregations (groupby, agg)1 min, 3 exercises
   16. Advanced GroupBy (transform, filter, named agg)4 min, 3 exercises
   17. Cross-Tabulation and Pivot Table Depth3 min, 3 exercises
   18. Hierarchical Indexing (MultiIndex)2 min, 3 exercises
   19. Reshaping Data (pivot, pivot_table, melt)1 min, 3 exercises
   20. Merging and Joining Data (merge, join, concat)2 min, 3 exercises
   21. Working with Dates and Times (to_datetime, dt accessor)1 min, 3 exercises
   22. Date Ranges, Frequencies and Shifting2 min, 3 exercises
   23. Time Zone Handling2 min, 3 exercises
   24. Periods and Period Arithmetic2 min, 3 exercises
   25. Resampling and Frequency Conversion2 min, 3 exercises
   26. Rolling and Moving Window Functions2 min, 3 exercises
4. Phase 4: Data Preprocessing and Cleaning12 lessons

   1. Understanding Data Quality2 min, 3 exercises
   2. Outlier Detection (IQR Method)1 min, 3 exercises
   3. Handling Outliers1 min, 3 exercises
   4. Feature Scaling (MinMax vs Standard)2 min, 3 exercises
   5. One-Hot Encoding1 min, 3 exercises
   6. Label Encoding1 min, 3 exercises
   7. Binning and Discretization1 min, 3 exercises
   8. Train-Test Split Concepts1 min, 3 exercises
   9. Preprocessing Pipeline (scikit-learn)1 min, 3 exercises
   10. Feature Engineering Basics1 min, 3 exercises
   11. Data Type Conversion and Validation2 min, 3 exercises
   12. Categorical Data Type3 min, 3 exercises
5. Phase 5: Data Visualization with Matplotlib12 lessons

   1. Introduction to Matplotlib1 min, 3 exercises
   2. Anatomy of a Plot1 min, 3 exercises
   3. Line Plot1 min, 3 exercises
   4. Bar Chart and Horizontal Bar1 min, 3 exercises
   5. Scatter Plot1 min, 3 exercises
   6. Histogram1 min, 3 exercises
   7. Pie Chart1 min, 3 exercises
   8. Subplots and Figure Size1 min, 3 exercises
   9. Axis Labels and Titles1 min, 3 exercises
   10. Legends and Colors1 min, 3 exercises
   11. Saving Plots as Images1 min, 3 exercises
   12. Matplotlib Mini Project (EDA charts pack)1 min, 3 exercises
6. Phase 6: Statistical Visualization with Seaborn14 lessons

   1. Phase 6 Overview - Statistical Visualization (Seaborn)1 min
   2. Introduction to Seaborn1 min, 3 exercises
   3. Seaborn vs Matplotlib1 min, 3 exercises
   4. Distribution Plots (displot, histplot)1 min, 3 exercises
   5. Kernel Density Estimation (KDE)1 min, 3 exercises
   6. Box Plots and Whiskers1 min, 3 exercises
   7. Violin Plots1 min, 3 exercises
   8. Count Plots1 min, 3 exercises
   9. Bar Plots in Seaborn1 min, 3 exercises
   10. Heatmaps for Correlation1 min, 3 exercises
   11. Pair Plots1 min, 3 exercises
   12. Joint Plots1 min, 3 exercises
   13. Regression Plots (lmplot, regplot)1 min, 3 exercises
   14. Facet Grids1 min, 3 exercises
7. Phase 7: Interactive Visualization with Plotly12 lessons

   1. Introduction to Plotly Express2 min, 3 exercises
   2. Interactive Line Charts1 min, 3 exercises
   3. Interactive Bar Charts1 min, 3 exercises
   4. Interactive Scatter Plots1 min, 3 exercises
   5. Bubble Charts1 min, 3 exercises
   6. Sunburst Charts1 min, 3 exercises
   7. 3D Scatter Plots2 min, 3 exercises
   8. Creating Dashboards with Plotly2 min, 3 exercises
   9. Choropleth Maps2 min, 3 exercises
   10. Interactive Histograms and Distributions1 min, 3 exercises
   11. Plotly Subplots and Facets2 min, 3 exercises
   12. Animations in Plotly2 min, 3 exercises
8. Phase 8: Statistics for Data Analytics16 lessons

   1. Introduction to Statistics for Data Analytics2 min, 3 exercises
   2. Descriptive Statistics (mean, median, variance)1 min, 3 exercises
   3. Probability Basics (events, conditional probability)2 min
   4. Distributions (normal, binomial, Poisson)1 min, 3 exercises
   5. Sampling and the Central Limit Theorem (CLT)2 min
   6. Confidence Intervals (CI)1 min, 3 exercises
   7. Hypothesis Testing (p-value, alpha, errors)1 min, 3 exercises
   8. t-test (independent and paired)1 min, 3 exercises
   9. ANOVA (one-way)1 min, 3 exercises
   10. Correlation vs Causation (Pearson, Spearman)1 min, 3 exercises
   11. Chi-Square Test (categorical association)1 min, 3 exercises
   12. Non-Parametric Tests (Mann-Whitney, Wilcoxon)1 min, 3 exercises
   13. A/B Testing Basics1 min, 3 exercises
   14. Statistical Power (intuition)2 min
   15. Statistics Mini Project (Analyze a Marketing Campaign)1 min, 3 exercises
   16. Linear Regression with statsmodels6 min, 3 exercises
9. Phase 9: SQL for Data Analytics9 lessons

   1. Introduction to SQL for Data Analytics2 min, 3 exercises
   2. SQL Basics (SELECT, WHERE, ORDER BY, LIMIT)1 min, 3 exercises
   3. Aggregations (COUNT, SUM, AVG) and GROUP BY2 min, 3 exercises
   4. Joins (INNER, LEFT) for Analytics1 min, 3 exercises
   5. Window Functions (OVER, PARTITION BY)1 min, 3 exercises
   6. CTEs (WITH) and Subqueries1 min, 3 exercises
   7. Date and Time Analytics in SQL1 min, 3 exercises
   8. SQL from Python (pandas + sqlite3)2 min, 3 exercises
   9. SQL Mini Project (Build a KPI Dashboard Query Set)1 min, 3 exercises
10. Phase 10: Data Analytics Projects15 lessons

    1. Exploratory Data Analysis (EDA) on Titanic2 min, 3 exercises
    2. Covid-19 Data Analysis & Visualization1 min, 3 exercises
    3. E-commerce Sales Analysis1 min, 3 exercises
    4. Netflix Movies & TV Shows Analysis1 min, 3 exercises
    5. Stock Market Analysis (Finance)1 min, 3 exercises
    6. Customer Churn Analysis1 min, 3 exercises
    7. Housing Price Prediction (Regression)1 min, 3 exercises
    8. Iris Flower Classification1 min, 3 exercises
    9. Uber Ride Data Analysis1 min, 3 exercises
    10. Credit Card Fraud Detection1 min, 3 exercises
    11. Twitter Sentiment Analysis1 min, 3 exercises
    12. Olympics Data Analysis2 min, 3 exercises
    13. HR Analytics Dashboard3 min, 3 exercises
    14. Spotify Song Popularity Analysis1 min, 3 exercises
    15. Global Terrorism Database Analysis1 min, 3 exercises