[huayang]

导入方式

import numpy as np
import pandas as pd

数据读取

csv文件

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings)

使用head()即可返回前几行数据

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings.head())

使用shape查看数据形状，返回（行数，列数）

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings.shape)

使用columns查看列名列表

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings.columns)

使用index查看索引列

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings.index)

使用dtypes查看每列数据类型

import numpy as np
import pandas as pd

fpath = open("ratings.csv")

ratings = pd.read_csv(fpath)

print(ratings.dtypes)

读取txt文件(需要自己指定分隔符列名)

import numpy as np
import pandas as pd

fpath = open("access_pvuv.txt")

asd = pd.read_csv(fpath,sep="\t",header=None,names=['qwe','asd','zxc'])

print(asd)#sep 指定列的分隔符 ，因为没有标题行所以header为none，names设定列名

读取excel文件

需要安装openpyxl这个库

import numpy as np
import pandas as pd

asd =  pd.read_excel('access_pvuv.xlsx')

print(asd)

pandas数据结构

Series

series是一种类似于一维数组的对象，他由一组数据（不同数据类型）
以及一组与之相关的数据标签（即索引）组成

仅有数据列表即可产生最简单的series

import numpy as np
import pandas as pd

s = pd.Series(['1','a','5.2','7'])
print(s)

values元素值的列表

dataframe：二位数据，整个表格，多行多列

[/huayang]

FROM：浅浅淡淡[hellohy]