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Pandas读取文件

时间:2019-08-05 21:49:33      阅读:108      评论:0      收藏:0      [点我收藏+]

标签:ddl   需求   book   read   指定   column   nan   读取文件   默认值   

# 1. 使用to_excel创建Excel文件
import pandas as pd
df = pd.DataFrame({‘id‘:[1,2,3],‘name‘:[‘zs‘,‘ls‘,‘ww‘]})
# 默认会有索引,将ID列设置成索引,会返回一个新的df,如果想要在原来的df上修改需要添加参数inplace=True
df = df.set_index(‘id‘)
df.to_excel(‘./output.xlsx‘)
print(‘end‘)
# 2. 使用pandas读取文件
import pandas as pd
# 此处需要安装依赖库xlrd
people = pd.read_excel(‘~/Desktop/People.xlsx‘)
print(‘获取文件中的行和列:‘,people.shape)
print("-"*20)
print(‘获取文件中的列名:‘,people.columns)
print("-"*20)
# 默认取前五行
print(‘获取文件中的前几行数据信息:‘,people.head())
print("-"*20)
print(‘获取文件中的后几行数据信息:‘,people.tail())
print("-"*20)
# 注意常见问题:
# 1. 读取的时候,默认会将第一行作为列名,我们可以修改
people = pd.read_excel(‘~/Desktop/People.xlsx‘,header = 1)
print(people.columns)
输出:
获取文件中的行和列: (19972, 6)
--------------------
获取文件中的列名: Index([‘ID‘, ‘Type‘, ‘Title‘, ‘FirstName‘, ‘MiddleName‘, ‘LastName‘], dtype=‘object‘)
--------------------
获取文件中的前几行数据信息:    ID      Type Title FirstName MiddleName    LastName
0   1  Employee   NaN       Ken          J     Sánchez
1   2  Employee   NaN     Terri        Lee       Duffy
2   3  Employee   NaN   Roberto        NaN  Tamburello
3   4  Employee   NaN       Rob        NaN     Walters
4   5  Employee   Ms.      Gail          A    Erickson
--------------------
获取文件中的后几行数据信息:           ID                 Type Title FirstName MiddleName    LastName
19967  20773  Individual Customer   NaN   Crystal        NaN         Guo
19968  20774  Individual Customer   NaN  Isabella          F  Richardson
19969  20775  Individual Customer   NaN   Crystal          S          He
19970  20776  Individual Customer   NaN   Crystal        NaN       Zheng
19971  20777  Individual Customer   NaN   Crystal        NaN          Hu
--------------------
Index([1, ‘Employee‘, ‘NULL‘, ‘Ken‘, ‘J‘, ‘Sánchez‘], dtype=‘object‘)
# 2. 使用pandas读取文件
import pandas as pd
#2. 如果第一行或者其他行不满足我们的需求时,我们可以自定义
# 第一种: 设置header为None,会使用默认的01234
people = pd.read_excel(‘~/Desktop/People.xlsx‘,header = None)
print(people.columns)
print("-"*20)
print(people.head())
print("-"*20)
# 第二种: 认为的设置默认值
people.columns = [‘ID1‘,‘Type1‘,‘Title1‘,‘FirstName1‘,‘MiddleName1‘,‘LastName1‘]
print(people.columns)
print("-"*20)
print(people.head())
print("-"*20)
# 重新存储
people.set_index(‘ID1‘,inplace = True)
print(people.head())
print("-"*20)
people.to_excel(‘./People1.xlsx‘)
print(‘end‘)
print("-"*20)
# 注意读取数据的时候,会将ID1右作为一列输出出来,所以可以在读取的时候用参数指定一下
people1 = pd.read_excel(‘./People1.xlsx‘,index_col = "ID1")
print(people1.head())
输出:
Int64Index([0, 1, 2, 3, 4, 5], dtype=‘int64‘)
--------------------
    0         1      2          3           4           5
0  ID      Type  Title  FirstName  MiddleName    LastName
1   1  Employee    NaN        Ken           J     Sánchez
2   2  Employee    NaN      Terri         Lee       Duffy
3   3  Employee    NaN    Roberto         NaN  Tamburello
4   4  Employee    NaN        Rob         NaN     Walters
--------------------
Index([‘ID1‘, ‘Type1‘, ‘Title1‘, ‘FirstName1‘, ‘MiddleName1‘, ‘LastName1‘], dtype=‘object‘)
--------------------
  ID1     Type1 Title1 FirstName1 MiddleName1   LastName1
0  ID      Type  Title  FirstName  MiddleName    LastName
1   1  Employee    NaN        Ken           J     Sánchez
2   2  Employee    NaN      Terri         Lee       Duffy
3   3  Employee    NaN    Roberto         NaN  Tamburello
4   4  Employee    NaN        Rob         NaN     Walters
--------------------
        Type1 Title1 FirstName1 MiddleName1   LastName1
ID1                                                    
ID       Type  Title  FirstName  MiddleName    LastName
1    Employee    NaN        Ken           J     Sánchez
2    Employee    NaN      Terri         Lee       Duffy
3    Employee    NaN    Roberto         NaN  Tamburello
4    Employee    NaN        Rob         NaN     Walters
--------------------
end
--------------------
        Type1 Title1 FirstName1 MiddleName1   LastName1
ID1                                                    
ID       Type  Title  FirstName  MiddleName    LastName
1    Employee    NaN        Ken           J     Sánchez
2    Employee    NaN      Terri         Lee       Duffy
3    Employee    NaN    Roberto         NaN  Tamburello
4    Employee    NaN        Rob         NaN     Walters
import pandas as pd
# 指定读哪个表
sheet = pd.read_excel(‘~/Desktop/sheet.xlsx‘,sheet_name=‘sheet2‘)
print(sheet.head())
print("-"*20)
# 3. 如果数据在表格中没有顶格写时
# skiprows : 跳过几行
# usecols: 使用那几列(C,指的就是Excel上的ABCD....)
book = pd.read_excel(‘~/Desktop/Books.xlsx‘,skiprows=3,usecols ="C:F")
print(book.head())
输出:
   ID  age
0   0   18
1   1   19
--------------------
   ID      Name  InStore
0 NaN  Book_001      NaN
1 NaN  Book_002      NaN
2 NaN  Book_003      NaN
3 NaN  Book_004      NaN
4 NaN  Book_005      NaN

 

Pandas读取文件

标签:ddl   需求   book   read   指定   column   nan   读取文件   默认值   

原文地址:https://www.cnblogs.com/imcati/p/11305719.html

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