This project is part of the tutorials from A2-Capacitacion
The present Exploratory Data Analysis (EDA) is an approach/philosophy for data analysis that employs a variety of techniques (mostly graphical) to:
- Maximize insight into a data set;
- Uncover underlying structure;
- Extract important variables;
- Detect outliers and anomalies;
- Test underlying assumptions;
- Develop parsimonious models; and
- Determine optimal factor settings.
- Pandas first impression (head)
- Pandas shape
- Mean
- Pandas describe
- Seaborn distplot (represents the overall distribution of continuous data variables)
- Pandas skew (calculates the skew for each column)
- Kurt (return unbiased kurtosis over requested axis)
- Scatter plot
- Box plot
- Seaborn heatmap
- Correlation coeficient
- Pair plot
- Pandas
- Matplotlib
- Seaborn
- NumPy
- Scipy
- Sklearn