python pandas series 02

序列series 理解

import pandas as pd
# dict 很像 key value pair d =（'x':100）
d =（'x':100）
s1 = pd.Series(d)
# index是 x value 是100

import pandas as pd
L1 = [100,200,300]
L2 = ['x','y','z']
s1 = pd.Series(L1， index = L2)
# 或者直接值放进去 s1 = pd.Series([100,200,300]， index = ['x','y','z'])

创建

import pandas as pd
s1 = pd.Series([1,2,3]， index = [1,2,3], name = 'A')
s1 = pd.Series([10,20,30]， index = [1,2,3], name = 'B')
s1 = pd.Series([100,200,3000]， index = [1,2,3], name = 'C')
df  = pd.DataFrame({s1.name:s1,s2.name:s2,s3.name:s3})
# 列的形式

import pandas as pd
s1 = pd.Series([1,2,3]， index = [1,2,3], name = 'A')
s1 = pd.Series([10,20,30]， index = [1,2,3], name = 'B')
s1 = pd.Series([100,200,3000]， index = [1,2,3], name = 'C')
df  = pd.DataFrame([s1,s2,s3])
# 行的形式

有空行的

import pandas as pd
from datetime import date, timedelta
books = pd.read_excel('books.xlsx',skiprows=3,usecols="C:F",index_col='ID', dtype={'ID':str,'Data':str})
start = date(2018,1,1)
for i in books.index:
	books['ID'].at[i]= i+1 # 那一列1，2，3，4...
	books['InStore'].at[i] = 'Yes' if i%2 ==0 else 'No'
	books['Date'].at[i] = start + timedelta(days = i)
# 如果是not a num 那么就是float类型 全转换成str类型

其他日期 年月（课时05）