行、列、单元格

数据字典

如：d={'x':100,'y':200,'z':300}

场景1

import pandas as pd
d={'x':100,'y':200,'z':300}
s1=pd.Series(d)
print( s1.index )
print( s1.data )
df=pd.DataFrame(s1)
df.to_excel("E:/test.xlsx")

场景2

import pandas as pd
L1=[100,200.300]
L2=['x','y','z']
s1=pd.Series(L1, index=L2)
df=pd.DataFrame(s1)
df.to_excel("E:/test.xlsx")

场景3

import pandas as pd
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.to_excel("E:/test.xlsx")

场景4

//跳过行和列
import pandas as pd
df = pd.read_excel("E:/test.xlsx", skiprows=3,usecols='C:F')
//查看type
print( type(df['ID']) )//返回应该是series, series有一个at属性
df['ID'].at[0] = 100
for i in df.index:
  df['ID'].at[i] = i+1
df.to_excel("E:/test.xlsx")

场景5

//跳过行和列
import pandas as pd
df = pd.read_excel("E:/test.xlsx", skiprows=3,usecols='C:F',dtype={'id':str})
//查看type
print( type(df['ID']) )//返回应该是series, series有一个at属性
df['ID'].at[0] = 100
for i in df.index:
  df['ID'].at[i] = i+1
  df['name'].at[i]='jack' if i%2==0 else 'tom'
df.to_excel("E:/test.xlsx")

场景6

//跳过行和列
import pandas as pd
df = pd.read_excel("E:/test.xlsx", skiprows=3,usecols='C:F',dtype={'id':str})
//查看type
print( type(df['ID']) )//返回应该是series, series有一个at属性
df['ID'].at[0] = 100
for i in df.index:
  df.at[i,'ID'] = i+1
  df.at[i,'NAME']='jack' if i%2==0 else 'tom'
df.to_excel("E:/test.xlsx")