easyeda 2.0

A useful tool to Exploratory Data Analysis

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: [e-mail]