Descriptive Statistics comprises of Measures of Central Tendency, Dispersion, Symmetry, Association, Normal Distribution, Misc.
Project description
Description
Descriptive Statistics is a wide range topic in the world of Statistics
Especially when we encounter with High-Volume data, It would be better to come up with summarized version of it.
Constraints:
- Features(Attributes/Columns): Needs to be of Integer/Float datatype.
Functionalities
- Measures of Central Tendency
- Mean
- Median
- Mode
- Measures of Dispersion
- Range
- Quartiles
- Q1
- Q2
- Q3
- Adjusted Q1
- Adjusted Q2
- Outliers
- Z-Score method
- IQR method
- Variance
- Standard Deviation
- Coefficient of Variation
- Measures of Symmetry
- Skew
- Left Skew
- Right Skew
- Symmetric
- Kurtosis
- Leptokurtic
- Mesokurtic
- Platykurtic
- Skew
- Measures of Association
- Covariance
- Correlation
- Normal Distribution (Empirical Rule)
- P68
- P95
- P97
- Multicollinearity
- VIF (Variance Inflation Factor)
- Misc
- Minimum
- Maximum
- Sum
- Count
- Missing
Output
How to import
pip install desc-stats
How to Use
from desc_stats import desc_stats
desc_stats(df, features) # list of features
desc_stats(df, feature1, feature2, ....) # Single feature
Contribute
pip install -e .[dev]
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