A unified module of frequently used data-science modules
Project description
Find yourself doing these over and over again everytime you start a new project or notebook?
pip3 install pandas scikit-learn matplotlib numpy statmodels scipy seaborn ...
and
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import scipy
...
dslibs eases your pain with an unified module that automatically installs and imports frequently used data science modules like numpy, pandas, scikit-learn, etc. in just a sec.
Installation
pip install dslibs-baosws
Usage
Just from dslibs import *:
>>> from dslibs import *
-------------------------------------------------------
Following modules was installed and imported by dslibs:
"numpy" as "np"
"pandas" as "pd"
"sklearn" as "skl"
"sklearn.preprocessing" as "spp"
"sklearn.model_selection" as "sms"
"sklearn.pipeline" as "spl"
"sklearn.metrics" as "smt"
"sklearn.feature_selection" as "sfs"
"matplotlib.pyplot" as "plt"
"statsmodels.api" as "sma"
"scipy" as "sp"
-------------------------------------------------------
>>> # now we can use 'pd' without 'import pandas as pd' as usual
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
>>> df
A B
0 1 4
1 2 5
2 3 6
Currently supported imports
| module | alias |
|---|---|
| numpy | np |
| pandas | pd |
| sklearn | skl |
| sklearn.preprocessing | spp |
| sklearn.model_selection | sms |
| sklearn.pipeline | spl |
| sklearn.metrics | smt |
| sklearn.feature_selection | sfs |
| matplotlib.pyplot | plt |
| statsmodels.api | sma |
| scipy | sp |
| seaborn | sns |
Project details
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