1.4 XlDataSeriesType参数 1.5 XlDataSeriesDate 二、Python脚本示例 importwin32com.clientaswinexcel=win.Dispatch("Excel.Application")excel.Visible=Trueworkbook=excel.Workbooks.Open("D:/Desktop/li.xlsx")sheet_1=workbook.Worksheets("sheet1")dataRange=sheet_1.Range("A1:A10")sheet_1.Cells(1,1).Valu...
A tuple is a container which holds a series of comma-separated values (items or elements) between parentheses. Tuples are immutable (i.e. you cannot change its content once created) and can hold mix data types. Creating Tuples To create an empty tuple or create a tuple with single elemen...
t=datetime.datetime.strptime(string, "%Y-%m-%d %H:%M:%S") print(f"type: {type(t)} and t: {t}") #type: <class 'datetime.datetime'> and t: 2022-01-01 11:30:09 1. 2. 3. 4. 格式字符串如下: 还可以使用strftime函数将datetime对象转换回特定格式的字符串表示。 t=datetime.datetime.n...
# Python程序将 series 转换为列表# 导入 pandas 模块import pandas as pd# 导入 regex 模块import re# 制作数据框data = pd.read_csv("nba.csv")# 删除空值以避免错误data.dropna(inplace = True)# 操作前存储 dtypedtype_before = type(data["Salary"])# 转换为列表salary_list = data["Salary"].tol...
python-pandas DataFrame,Series笔记1 包含头文件 #!/usr/bin/evn python import numpy as np import pandas as pd Series """Series Series is a one-dimensional labeled array capable of holding any data type(integers, strings, floating point numbers, Python objects, etc.). The axis labels are ...
classpandas.Series(data=None,index=None,dtype=None,name=None,copy=None,fastpath=False)[source]类...
Series组成的字典data1 = {'one':pd.Series(np.random.rand(2)),'two':pd.Series(np.random.rand(3))}# 没有设置index的Seriesdata2 = {'one':pd.Series(np.random.rand(2), index = ['a','b']),'two':pd.Series(np.random.rand(3),index = ['a','b','c'])}# 设置了index的Series...
一、Pandas数据结构之Series: 类似于表格中的一个列(column),类似于一维数组,语法: pd.Series(data,index,dtype,name,copy) 1. 二、创建Series对象 点击查看代码 s = pd.Series(data=np.random.randn(5),index=['a','b','c','d','e'],dtype='float64',name='这是一个Series') ...
print(type(t["b"])) 输出为: <class 'pandas.core.series.Series'> 说明b列数据类型为Series。 3.12 切片(重点) 用loc可以进行各种切片(块)。这里注意loc后面是[] 某行的切片 print(t.loc["B", :]) 输出为: a 11 b 12 c 13 d 14 e 15 Name: B, dtype: int64 注意和上面3.10的区别 切块...
数据(Data):实际存储的数据,可以是标量、列表、字典或 NumPy 数组。 示例代码 1:创建一个简单的 Series 对象 importpandasaspd# 使用标量创建 Series 对象data=7series=pd.Series(data)print(series) 1. 2. 3. 4. 5. 6. 输出: 0 7 dtype: int64 ...