文件处理

主目录

文件处理:  csv, table, json, txt, db

这里面全是死的东西，在这几个例子最常用的是.csv   .dat   .txt   文件，再牛逼点儿的使用json转成对象

import pandas as pd
import json
path = 'datasets/bitly_usagov/example.txt'
open(path).readline()

records = [json.loads(line) for line in open(path)]
records[0]

#----------------------------------#

pd.options.display.max_rows = 10
unames = ['user_id', 'gender', 'age', 'occupation', 'zip']
rnames = ['user_id', 'movie_id', 'rating', 'timestamp']
mnames = ['movie_id', 'title', 'genres']
user= pd.read_table('datasets/movielens/users.dat', sep='::', header=None, names=unames)
ratings = pd.read_table('datasets/movielens/ratings.dat', sep='::', header=None, names= rnames)
movies = pd.read_table('datasets/movielens/movies.dat', sep='::', header=None, names=mnames)
user[:5]

#----------------------------------#

names1880 = pd.read_csv('datasets/babynames/yob1880.txt', names = ['name', 'sex', 'births'])
names1880.head()

#----------------------------------#

db = json.load(open('datasets/usda_food/database.json'))  # 32M的数据
len(db)

#----------------------------------#

fec = pd.read_csv('datasets/fec/P00000001-ALL.csv')
fec.info()

详细中文参考:  https://www.jianshu.com/p/047d8c1c7e14

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