in statistics, exploratory data analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. Exploratory data analysis was promoted by John Tukey to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from initial data analysis (IDA) which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed. EDA encompasses IDA.
Typical graphical techniques used in this repository are
- Scatter plot
- Bar plot
- Stacked plot
- Pie plot
- Reg plot
- Lm plot
- Distplot
- Histogram
- Pair plot
- Relation plot
- Cat plot
- Swarm plot
- Box plot
- Kde plot
- Heatmap Correlation
- Countplot
- Violin plot
- line plot
- Area plot
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