Data Cleaning 1

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1. Read mutiple data files;

　　import pandas as pd

　　data_files = [
　　"ap_2010.csv",
　　"class_size.csv",
　　"demographics.csv",
　　"graduation.csv",
　　"hs_directory.csv",
　　"sat_results.csv"
　　]

　　data = {}

　　for f in data_files:
　　file = pd.read_csv("schools/{0}".format(f)) #Format string syntax
　　f = f.replace(".csv","")#Delete all the .csv and save as file name
　　data[f] = file

2. Read .txt file and combine function:

　　all_survey = pd.read_csv("schools/survey_all.txt",delimiter = "\t", encoding = "windows-1252") #what is the meaning of delimiter and encoding?
　　d75_survey = pd.read_csv("schools/survey_d75.txt",delimiter = "\t", encoding = "windows-1252") 
　　survey = pd.concat([all_survey,d75_survey],axis = 0) #combine function

Data Cleaning 1

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原文地址：http://www.cnblogs.com/kingoscar/p/5975884.html