系统:Windows 7 语言版本:Anaconda3-4.3.0.1-Windows-x86_64 编辑器:pycharm-community-2016.3.2 pandas:0.19.2
Part 1:场景介绍
Part 2:代码
import pandas as pd
import os
dict_1 = {"time": ["2019-11-02", "2019-11-03", "2019-11-04", "2019-11-05",
"2019-12-02", "2019-12-03", "2019-12-04", "2019-12-05"],
"pos": ["A", "A", "B", "B", "C", "C", "C", "D"],
"value1": [10, 20, 30, 40, 50, 60, 70, 80]}
df_1 = pd.DataFrame(dict_1, columns=["time", "pos", "value1"])
print("原数据", "\n", df_1, "\n")
# 输出到Excel
current_address = os.path.dirname(os.path.abspath(__file__))
excel_name = "df.xlsx"
excel_address = os.path.join(current_address, excel_name)
df_1.to_excel(excel_address)
excel_name_2 = "df_2.xlsx"
excel_address_2 = os.path.join(current_address, excel_name_2)
df_2 = df_1.head(3)
df_2.to_excel(excel_address_2)
# 读Excel数据
df_3 = pd.read_excel(excel_address)
print(df_3)
excel_name_4 = "test.xlsx"
excel_address_4 = os.path.join(current_address, excel_name_4)
df_4 = pd.read_excel(excel_address_4, sheetname="ceshi", header=0)
print(df_4)
代码截图
excel_address
excel_address_2
test.xlsx
代码运行命令窗口输出
Part 3:部分代码解读
df_1.to_excel(excel_address)
,通过to_excel函数即可,若只是看一下数据结构,可以只输出Df的一部分,df_2 = df_1.head(3)
即表示df_1的前3行df_3 = pd.read_excel(excel_address)
,通过pd.read_excel,默认读取第1张表。当被读取Excel有多张表格时,可以指定拟读取工作表,sheetname="ceshi"
,df_4 = pd.read_excel(excel_address_4, sheetname="ceshi", header=0)
,即该函数有多个参数可以根据需要进行设置read_excel参数
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