1，Introduction
The easyeda is a simple but useful tool to do Exploratory Data Analysis in Machine Learning. It can be used in both classification task and regression task.
2，Use Example
First, you can use pip to install easyeda.
pip install easyeda
Then, you can use it like below.
from easyeda import eda
import pandas as pd
from sklearn import datasets
from sklearn.model_selection import train_test_split
##
boston = datasets.load_boston()
df = pd.DataFrame(boston.data,columns = boston.feature_names)
df["label"] = boston.target
dftrain,dftest = train_test_split(df,test_size = 0.3)
dfeda = eda(dftrain,dftest,language="Chinese")
3，Contact to the author
Github: https://github.com/lyhue1991/easyeda
Email: lyhue1991@163.com
1 maintainer
Metadata
1 maintainer
Release files for easyeda 2.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| easyeda-2.0.tar.gz | 3.7 kB | Without provenance | Details for easyeda-2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| easyeda-2.0-py3-none-any.whl | Python 3 | none | any | Details for easyeda-2.0-py3-none-any.whl |
Total release size: 8.4 kB
Release files / easyeda-2.0.tar.gz
| Download URL | easyeda-2.0.tar.gz |
|---|---|
| Size | 3.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / easyeda-2.0-py3-none-any.whl
| Download URL | easyeda-2.0-py3-none-any.whl |
|---|---|
| Size | 4.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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