pandas 读取文件

pandas 读取文件

文档参考《深入浅出 Pandas 利用Python 进行数据处理与分析》，还有pandas 官方文档，https://www.pypandas.cn/docs/
https://pandas.pydata.org/
https://www.gairuo.com/p/pandas

1 读取的 csv 文件

import numpy as np
import pandas as pd

分类

​

读取本地相对路径

df = pd.read_csv('tmp.csv')
df.head()

读取本地绝对路径

df2 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/tmp.csv')
df2.head()

读取网络文档

# pd.read_csv('data/my/my.data')

df = pd.read_csv('https://www.gairuo.com/file/data/dataset/GDP-China.csv')
df.head()

分隔符

df2 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team3.csv')
df2.head()

df3 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team3.csv',sep = 't')
df3.head()

表头

df6 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv')
df6.head()

df7 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',header = 1)
df7.head()

df8 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',header = [0,1,3])
df8.head()

列名

注意与 col 参数的区别

df9 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',names = ['name','team'])
df9.head()

如果文件不包含列名，那么应该设置header=None，列名列表中 不允许有重复值。

df9 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',names = ['name','team'],header = None)
df9.head()

df10 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',index_col = False)
df10.head()

df10 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',index_col = 0)
df10.head()

df10 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',index_col = ['name','team'])
df10.head()

df10 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',index_col = [0,1])
df10.head()

使用部分列

df11 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = [0,1])
df11.head()

df12 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = ['name','Q1'])
df12.head()

指定列顺序，其实是df的筛选功能

df12 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = ['name','Q1'])[['Q1','name']]
df12.head()

返回序列

将squeeze设置为True，如果文件只包含一列，则返回一个Series， 如果有多列，则还是返回DataFrame。

df13 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = ['name','Q1'],squeeze = True)
df13.head()

df14 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = ['name'],squeeze = True)
df14.head()

表头前缀

如果原始数据没有列名，可以指定一个前缀加序数的名称

df14 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',prefix = 'c_',header = None)
df14.head()

数据类型

df15 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv')
df15.dtypes

name    object
team    object
Q1       int64
Q2       int64
Q3       int64
Q4       int64
dtype: object

df16 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',dtype = {'Q1':np.float64})
df16.dtypes

name     object
team     object
Q1      float64
Q2        int64
Q3        int64
Q4        int64
dtype: object

df16.head()

df16 = pd.read_csv('/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team2.csv',usecols = [2,3,4,5],dtype = np.float64)
df16.head()

df16.dtypes

Q1    float64
Q2    float64
Q3    float64
Q4    float64
dtype: object

读取指定行

pd.read_csv(data, nrows = 1000)

类似列表的序列或者可调用对象

跳过前三行 pd.read_csv(data, skiprows=2)

跳过前三行 pd.read_csv(data, skiprows=range(2))

跳过指定行 pd.read_csv(data, skiprows=[24,234,141])

跳过指定行 pd.read_csv(data, skiprows=np.array([2, 6, 11]))

隔行跳过 pd.read_csv(data, skiprows=lambda x: x % 2 != 0)

Excel

url = '/Users/xinmin/DataAnalysis/1.深入浅出Pandas/team.xlsx'
df2 = pd.read_excel(url)
df2.head()

url2 = '/Users/xinmin/DataAnalysis/1.深入浅出Pandas/tmp.xlsx'
df3 = pd.read_excel(url2)
df3.head()

df3 = pd.read_excel(url2,sheet_name = 1)
df3.head()

df4 = pd.read_excel(url2,sheet_name ='Sheet2')
df4.tail()

df5 = pd.read_excel(url2,sheet_name = [0,1,'Sheet2'])
df5

{0:         name team  Q1  Q2  Q3  Q4
 0      Liver    E  89  21  24  64
 1       Arry    C  36  37  37  57
 2        Ack    A  57  60  18  84
 3      Eorge    C  93  96  71  78
 4        Oah    D  65  49  61  86
 ..       ...  ...  ..  ..  ..  ..
 95   Gabriel    C  48  59  87  74
 96   Austin7    C  21  31  30  43
 97  Lincoln4    C  98  93   1  20
 98       Eli    E  11  74  58  91
 99       Ben    E  21  43  41  74
 
 [100 rows x 6 columns],
 1:       Liver  E  89  21  24  64
 0      Arry  C  36  37  37  57
 1       Ack  A  57  60  18  84
 2     Eorge  C  93  96  71  78
 3       Oah  D  65  49  61  86
 4    Harlie  C  24  13  87  43
 5      Acob  B  61  95  94   8
 6      Lfie  A   9  10  99  37
 7    Reddie  D  64  93  57  72
 8     Oscar  A  77   9  26  67
 9       Leo  B  17   4  33  79
 10    Logan  B   9  89  35  65
 11   Archie  C  83  89  59  68
 12     Theo  C  51  86  87  27
 13   Thomas  B  80  48  56  41
 14    James  E  48  77  52  11
 15   Joshua  A  63   4  80  30
 16    Henry  A  91  15  75  17
 17  William  C  80  68   3  26
 18      Max  E  97  75  41   3
 19    Lucas  A  60  41  77  62
 20    Ethan  D  79  45  89  88,
 'Sheet2':       Liver  E  89  21  24  64
 0      Arry  C  36  37  37  57
 1       Ack  A  57  60  18  84
 2     Eorge  C  93  96  71  78
 3       Oah  D  65  49  61  86
 4    Harlie  C  24  13  87  43
 5      Acob  B  61  95  94   8
 6      Lfie  A   9  10  99  37
 7    Reddie  D  64  93  57  72
 8     Oscar  A  77   9  26  67
 9       Leo  B  17   4  33  79
 10    Logan  B   9  89  35  65
 11   Archie  C  83  89  59  68
 12     Theo  C  51  86  87  27
 13   Thomas  B  80  48  56  41
 14    James  E  48  77  52  11
 15   Joshua  A  63   4  80  30
 16    Henry  A  91  15  75  17
 17  William  C  80  68   3  26
 18      Max  E  97  75  41   3
 19    Lucas  A  60  41  77  62
 20    Ethan  D  79  45  89  88}

df6 = pd.read_excel(url2,header = None)
df6.head()

df7 = pd.read_excel(url2,header = None,sheet_name = 'Sheet2')
df7.head()

df8 = pd.read_excel(url2,header = [0,1])
df8

99 rows × 6 columns

数据输出

输出Excel 文件path_to_excel.xlsx,sheet_name 是tmp ,index = False 不设置索引，header = None 是不设置表头

df18.to_excel(‘path_to_excel.xlsx’,sheet_name = ‘tmp’,index = False,header = None)

将多个df分不同sheet导入一个Excel文件中

with pd.ExcelWriter(‘path_to_file.xlsx’) as writer:
df1.to_excel(writer, sheet_name=‘Sheet1’)
df2.to_excel(writer, sheet_name=‘Sheet2’)

最后

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