先前發文
DAY 01 : 參賽目的與規劃
DAY 02 : python3 virtualenv 建置
DAY 03 : python3 request
DAY 04 : 使用beautifulsoup4 和lxml
DAY 05 : select 和find 抓取tag
DAY 06 : soup解析後 list取值
DAY 07 : request_header_cookie 通過網頁18限制
DAY 08 : ppt內文爬取
DAY 09 : 資料處理 split replace strip
DAY 10 : python csv 寫入 和dict 合併
DAY 11 : python class function
DAY 12 : crawl 框架 scrapy 使用
DAY 13 : scrapy 架構
DAY 14 : scrapy pipeline data insert mongodb
DAY 15 : scrapy middleware proxy
DAY 16 : scrapy selenium
DAY 17 : scrapy 爬取js畫面資料(二)
DAY 18 : scrapy splash 爬取js畫面資料(三)
DAY 19 : python .env 使用
DAY 20 : python chartify 資料視覺化套件
DAY 21 : python3 pandas 資料處理

pip3 install pandas
pip3 install mlxtend xlrd

# -*- coding: utf-8 -*-

import pandas as pd
import numpy as np
from mlxtend.frequent_patterns import apriori
from mlxtend.frequent_patterns import association_rules


# header = 
# read 檔案
df1 = pd.read_csv('data/test1.txt', sep=",", chunksize = 1000, header=None,names=["Sequence", "Start", "End", "Coverage"])
# print(df1)

df2 = pd.read_csv('data/test2.txt', sep=",", chunksize = 1000, header=None,names=["Sequence", "Start", "End", "Coverage"])

df = pd.DataFrame(columns=[]) 

for df1 in df1:
#     print(df1)
    print(type(df1))
    df3 = pd.concat([df,df1],ignore_index=True) 
for df2 in df2: 
#     print(df2)
    print(type(df2))
    df4 = pd.concat([df,df2],ignore_index=True) 
    
print(type(df1))
print(type(df2))
print(type(df3))
print(type(df4))

res = pd.concat([df3, df4],  axis=0)
res['count'] = 1
print(res)