python - 如何使用pandas python根据给定的IP地址将大型excel文件拆分为多个工作表

Question

我是 pandas 和 python 的新手，所以遇到了一些麻烦。我有一个大的 excel 文件，我需要使用 python 脚本将其分成多个工作表。我必须根据数据中给出的 IP 地址进行划分。我无法弄清楚如何做到这一点，并希望得到一些帮助和指导。
我以前不知道使用 python 或任何库。这就是我所做的，但为每一行创建了工作簿。

import pandas as pd
df = pd.read_excel("D:/Users/Zakir/Desktop/MyNotebooks/Legacy.xls", sheet_name="Total", header=0, names=None, index_col=None, parse_cols=None, usecols=None, squeeze=False, dtype=None, engine=None, converters=None, true_values=None, false_values=None, skiprows=None, nrows=None, na_values=None, keep_default_na=True, verbose=False, parse_dates=False, date_parser=None, thousands=None, comment=None, skipfooter=0, convert_float=True, mangle_dupe_cols=True)

writer = pd.ExcelWriter('D:/Users/Zakir/Desktop/MyNotebooks/pandas_simple.xlsx', engine='xlsxwriter')
for index, row in df.iterrows():
    df1 = df.iloc[[index]]
    df1.set_index('Number',inplace=True)
    df1.to_excel(writer,  sheet_name=row['IPAddress'])
writer.save()

This is the kind of excel file i have. over 5000 rows. There are 60 groups of ip addresses and have to divide each group into its own worksheet

Answer 1

如果您有足够的内存，一种解决方案:

from pandas import ExcelWriter
df = pd.read_excel('file',sheet_name="Total", header=0, #other settings.....#)
writer = ExcelWriter('E:/output.xlsx',engine='xlsxwriter')
print(df)
def writesheet(g):
    a = g['IPAddress'].tolist()[0]
    g.to_excel(writer, sheet_name=str(a), index=False)# index = True if you want to keep index


df.groupby('IPAddress').apply(writesheet)
writer.save()