数据分析 A-Z - 30 天内成为数据分析师
Data Analysis A-Z - Become Data Analyst in 30 Days
- 2. What is Data Analysis
- 1. Day 1 Data analysis and its characteristics
- 2. Day 2 Complete data analysis work-flow
- 3. Stage 1 Data Cleaning A - Z
- 1. Day 3 Loading dataset in your jupyter notebook
- 2. Day 4 Dealing with missing values
- 3. Day 5 Dealing with inconsistent values
- 4. Day 6 Dealing with miss-identified data types
- 5. Day 7 Dealing with duplicated data
- 4. Stage 2 Data Manipulation A-Z
- 1. Day 8 Learn data sorting and arrangement
- 2. Day 9 Learn conditional data filtering
- 3. Day 10 Learn to merge extra variables
- 4. Day 11 Learn to concatenate extra data
- 5. Stage 3 Exploratory Data Analysis A-Z
- 1. Day 12 Exploring value counts analysis method
- 2. Day 13 Exploring descriptive statistics analysis method
- 3. Day 14 Exploring group by analysis method
- 4. Day 15 Exploring pivot table analysis method
- 5. Day 16 Exploring crosstabulation analysis method
- 6. Day 17 Exploring correlation analysis method
- 6. Stage 4 Understanding Statistical Data Analysis A-Z
- 1. Day 18 Various aspects of hypothesis testing
- 2. Day 19 Understand confidence level, significance level and p-value
- 3. Day 20 Understand complete steps in hypothesis testing
- 7. Stage 5 Data Transformation A-Z
- 1. Day 21 Testing normal distribution of numeric variables
- 2. Day 22 Square root transformation for normal distribution
- 3. Day 23 Logarithmic transformation for normal distribution
- 4. Day 24 Box-cox transformation for normal distribution
- 5. Day 25 Yeo-Johnson transformation for normal distribution
- 8. Stage 6 Hypothesis Testing A-Z
- 1. Day 26 One way between groups ANOVA
- 2. Day 27 Pearson product-moment correlation coefficient
- 3. Day 28 Multiple linear regression analysis with statsmodel.api
- 9. Tips, Tricks and Resources!
- 1. ChatGPT for smooth python coding in Data Analysis