https://github.com/lyhue1991/easyeda
a simple but useful tool to do Exploratory Data Analysis
https://github.com/lyhue1991/easyeda
Last synced: 5 months ago
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a simple but useful tool to do Exploratory Data Analysis
- Host: GitHub
- URL: https://github.com/lyhue1991/easyeda
- Owner: lyhue1991
- License: mit
- Created: 2019-10-19T02:33:32.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-10-23T16:29:28.000Z (almost 6 years ago)
- Last Synced: 2025-04-12T21:37:41.218Z (6 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 195 KB
- Stars: 12
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## 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.
```bash
pip install easyeda
```
Then, you can use it like below.
```python
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