Harry’s Journey in Python

Current Ongoing Learnings & Projects

1. Linear Regression & Logistic Regression for People Analytics (Offline)

2. People Turnover Forecast (folked from Burunokatekawa)

Past Learnings & Projects

1. Automated Stock Analysis and Investment by Python

2. Importing Raw Data and Pre-Data Validation

3. Univariate Analysis (Numerical Variable) by Pandas

• Mean
• Median
• Mode
• Count
• Max
• Min
• Quantiles
• Varirance
• Standrad Deviation
• Range, Interquartile Range
• Histogram

4. Unvariate Analysis (Numerical Variable) by Pandas, Sklearn

• Skewness
• Data Standardization (Z-Score Distribution)

5. Univariate Analysis (Categorical Variable) by Pandas

• Count
• Frequency
• Percentage
• Bar Chart
• Pie Chart

6. Data Clearning (Missing Values) by Pandas

• Removing N/A (Counting N/A)
• Replacing N/A with 0
• Replacing N/A with Mean

7. Data Clearning (Outliners) by Pandas, Scipy

• Filtering Data (Advanced Filter)
• Detection by Boxplot
• Detection by Z-Score
• Capping
• Flooring

8. Bi-variate Analysis (Numerical and Numerical) by Pandas

• Scatter Plot
• Scatter Matrix
• Covariance, Correlation

9. Bi-variate Analysis (Categorical and Categorical) by Pandas, Matplotlib

• Cross-Tab
• Proportion Table
• Slacked Chart
• Bar Chart
• Column Chart
• Mosaic Plot

10. Bi-variate Analysis (Numerical and Categorical) by Pandas, Matplotlib

• Descriptive Statistics
• Box Plot

11. Hypothesis Testing by Scipy

• One Sample T-Test
• Paired T-Test
• Chi-Squiare
• ANOVA

12. Variable Creation by Pandas, Numpy

• Tenure
• Compa Ratio
• Dummy Variable (Converting Category into Integer)

13. Variable Transformation by Pandas, Matplotlib, Scipy, Numpy

• Normalization
• Log Transformation
• Square Root Transformation
• Cube Root Transformation
• Binning*