Data Science Kit - Kitbag
KITBAG is a helpful library where you can find basic data science functions under three main headings. Three main headings are given below. The titles are given below;
- Measurement Units
- Arithmetic Mean
- Geometric Mean
- Harmonic Mean
- Median
- Mode
- Variance
- Standart Deviation
- Find Minimum Value In List
- Find Maximum Value In List
- Kurtosis
- Skewnewss
- Quantiles
- Range Of Change
- Covariance
- Correlation
- Exploratory Data Analysis
- Copy Dataset
- Show Head & Tail Values
- Structural Information
- Variable Types
- Object To Categorical
- Observation Values Size
- Variable Values Size
- Size Of Dataset
- Dimension Of DataFrame
- Dimension Of Series
- Variable Names Of Dataset
- Descriptive Statistics Of Dataset
- Descriptive Statistics Of Numerical Variable
- Descriptive Statistics Of Categorical Variable
- Select Categorical Variables
- Select Numerical Variables
- Frequency Of Categorical Variables
- Categorical Variables Percentage Of Dataset
- Find Unique Categorical Variables
- Frequency Unique Categorical Variables
- Measure Operations Of Single Categorical Variables With All Numerical Variables
- Measure Operations Of Single Categorical Variables Single Numerical Variables
- Measure Operations Of Multiple Categorical Variables Single Numerical Variables
- Create And Sort Rank Variables
- Select Range Row By Index
- Data Operations
- Missing Values
- Is There Any NAN Values
- Total NAN Values
- Percentage NAN Values
- Drop NAN Values In Row
- Drop NAN Values In Column
- Fill NAN Values Column
- Fill NAN Values All Dataset
- Fil NAN Values KNN
- Fil NAN Values EM
- Outlier Values
- Select Lower Outlier Values - According to the specified Column
- Select Upper Outlier Values - According to the specified Column
- Select All Outlier Values - According to the specified Column
- Delete Outlier Values
- Fill Mean Value All Outlier Values
- Fill Suppression Method All Outlier Values
- Local Outlier Factor
- Local Outlier Factor Suppression Method
- Variables Standartization
- Numerical Variables Standartization
- Numerical Variables Normalization
- Numerical Variables Transformation
- Numerical Variables Binarize
- Numerical Variables To Categorical Variables
- Encoding Operations
- Ordinal Encoder
- Label Encoder
- Where Encoder
- Onehot Encoder
- Missing Values
Metadata
Release files for data-science-kit 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| data-science-kit-0.0.1.tar.gz | 9.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| data_science_kit-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 18.4 kB
Release files / data-science-kit-0.0.1.tar.gz
| Download URL | data-science-kit-0.0.1.tar.gz |
|---|---|
| Size | 9.3 kB |
| Tags | Source |
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twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.23.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6
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Release files / data_science_kit-0.0.1-py3-none-any.whl
| Download URL | data_science_kit-0.0.1-py3-none-any.whl |
|---|---|
| Size | 9.0 kB |
| Tags | Python 3 |
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twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.23.0 requests-toolbelt/0.9.1 tqdm/4.41.1 CPython/3.7.6
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