pandas vs excel

01. Create a file

import pandas as pd

df = pd.DataFrame({'ID':[1,2,3],'Name':['Tim','','Nick']}) #创建DataFrame

df


df = df.set_index('ID')

df


df.to_excel(r"C:\Users\Administrator\Desktop\output.xlsx") #写入到Excel

02. read the file

import pandas as pd

people = pd.read_excel(r"C:\Users\Administrator\Desktop\people.xlsx") #读取Excel文件

Print (people.shape) # output ranks number 
Print (people.columns) # output column name 
Print (people.head ()) # output of the first five rows 
Print (people.tail (3)) # View data in the last three lines 

people pd.read_excel = (r " C: \ the Users \ Administrator \ Desktop \ people.xlsx " , header = 1) # read Excel file, the default behavior to second column name 

people = pd.read_excel (r " C: \ the Users \ Administrator \ Desktop \ people.xlsx " , header = None) # read Excel file, the default name is not listed 
# will automatically use 1,2,3 .... instead of the column name 

people.columns = [ ' ID','Type','FirstName','MiddleName','LastName'] #设置列名

people = people.set_index('ID')
people.set_index ( ' ID ' , InPlace = True) # directly modify the original DataFrame, does not generate a new dataframe

people

people.to_excel(r"C:\Users\Administrator\Desktop\output.xlsx")

DF = pd.read_excel (R & lt " C: \ the Users \ Administrator \ Desktop \ output.xlsx " , index_col = ' ID ' ) # indicates when the index is read the file ID column

03. rows, columns, cells,

import pandas as pd

s1 = pd.Series()
s1.index
'''
Index([], dtype='object')
'''

d = {'x':100,'y':200,'z':300}

print(d.keys())
print(d.values())
print(d['x'])
'''
dict_keys(['x', 'y', 'z'])
dict_values([100, 200, 300])
100
'''

s1 = pd.Series(d)

print(s1.index)
print(s1.data)
s1
'''
Index(['x', 'y', 'z'], dtype='object')
<memory at 0x00000187AE02D648>

x    100
and 200
300
dtype: int64
'''

L1 = [100,200,300]
L2 = [ ' x ' , ' and ' , ' z ' ]

s1 = pd.Series(L1,index=L2)
s1.index
'''
Index(['x', 'y', 'z'], dtype='object')
'''

s1 = pd.Series([100,200,300],index=['x','y','z'])
s1.index
'''
Index(['x', 'y', 'z'], dtype='object')
'''

s1 = pd.Series([1,2,3],index=[1,2,3],name='A')
s2 = pd.Series([10,20,30],index=[1,2,3],name='B')
s3 = pd.Series([100,200,300],index=[1,2,3],name='C')

df = pd.DataFrame({s1.name:s1,s2.name:s2,s3.name:s3})
df


s1 = pd.Series([1,2,3],index=[1,2,3],name='A')
s2 = pd.Series([10,20,30],index=[1,2,3],name='B')
s3 = pd.Series([100,200,300],index=[1,2,3],name='C')

df = pd.DataFrame([s1,s2,s3])
df


s1 = pd.Series([1,2,3],index=[1,2,3],name='A')
s2 = pd.Series([10,20,30],index=[1,2,3],name='B')
s3 = pd.Series([100,200,300],index=[2,3,4],name='C')

df = pd.DataFrame({s1.name:s1,s2.name:s2,s3.name:s3})
df

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