2. Exploratory Data Analysis in Python

Steps in EDA

Here is a list of steps involved in EDA :

•     Loading the necessary libraries and setting them up

•     Data collection

•     Data wrangling/munging

•     Data cleaning

•     Obtaining descriptive statistics

•     Visual inspection of the data

•     Data cleaning

•     Advanced visualization techniques

 

%matplotlib inline
! pip install mpld3
import numpy as np
import pandas as pd
from scipy import stats
import seaborn as sn
import matplotlib.pyplot as plt

# Jupyter의 matplotlib 차트 내에서 확대/축소를 활성화
import mpld3
mpld3.enable_notebook()

import warnings
warnings.filterwarnings('ignore')

# pandas DataFrames 최대 row, column 지정
pd.set_option('display.max_rows', 2)
pd.set_option('display.max_columns', 7)

 

 

 

A.csv

0.10MB

B.csv

0.09MB

C.csv

0.06MB

 

 

eda.ipynb

1.83MB