导读 | 这篇文章主要介绍了VBA处理数据与Python Pandas处理数据案例比较,本文通过实例代码给大家介绍的非常详细,具有一定的参考借鉴价值,需要的朋友可以参考下 |
需求:
现有一个 csv文件,包含'CNUM'和'COMPANY'两列,数据里包含空行,且有内容重复的行数据。
要求:
1)去掉空行;
2)重复行数据只保留一行有效数据;
3)修改'COMPANY'列的名称为'Company_New‘;
4)并在其后增加六列,分别为'C_col',‘D_col',‘E_col',‘F_col',‘G_col',‘H_col'。
一,使用 Python Pandas来处理:
import pandas as pd import numpy as np from pandas import DataFrame,Series def deal_with_data(filepath,newpath): file_obj=open(filepath) df=pd.read_csv(file_obj) # 读取csv文件,创建 DataFrame df=df.reindex(columns=['CNUM','COMPANY','C_col','D_col','E_col','F_col','G_col','H_col'],fill_value=None) # 重新指定列索引 df.rename(columns={'COMPANY':'Company_New'}, inplace = True) # 修改列名 df=df.dropna(axis=0,how='all') # 去除 NAN 即文件中的空行 df['CNUM'] = df['CNUM'].astype('int32') # 将 CNUM 列的数据类型指定为 int32 df = df.drop_duplicates(subset=['CNUM', 'Company_New'], keep='first') # 去除重复行 df.to_csv(newpath,index=False,encoding='GBK') file_obj.close() if __name__=='__main__': file_path=r'C:\Users\12078\Desktop\python\CNUM_COMPANY.csv' file_save_path=r'C:\Users\12078\Desktop\python\CNUM_COMPANY_OUTPUT.csv' deal_with_data(file_path,file_save_path)
二,使用 VBA来处理:
Option Base 1 Option Explicit Sub main() On Error GoTo error_handling Dim wb As Workbook Dim wb_out As Workbook Dim sht As Worksheet Dim sht_out As Worksheet Dim rng As Range Dim usedrows As Byte Dim usedrows_out As Byte Dim dict_cnum_company As Object Dim str_file_path As String Dim str_new_file_path As String 'assign values to variables: str_file_path = "C:\Users\12078\Desktop\Python\CNUM_COMPANY.csv" str_new_file_path = "C:\Users\12078\Desktop\Python\CNUM_COMPANY_OUTPUT.csv" Set wb = checkAndAttachWorkbook(str_file_path) Set sht = wb.Worksheets("CNUM_COMPANY") Set wb_out = Workbooks.Add wb_out.SaveAs str_new_file_path, xlCSV 'create a csv file Set sht_out = wb_out.Worksheets("CNUM_COMPANY_OUTPUT") Set dict_cnum_company = CreateObject("Scripting.Dictionary") usedrows = WorksheetFunction.Max(getLastValidRow(sht, "A"), getLastValidRow(sht, "B")) 'rename the header 'COMPANY' to 'Company_New',remove blank & duplicate lines/rows. Dim cnum_company As String cnum_company = "" For Each rng In sht.Range("A1", "A" & usedrows) If VBA.Trim(rng.Offset(0, 1).Value) = "COMPANY" Then rng.Offset(0, 1).Value = "Company_New" End If cnum_company = rng.Value & "-" & rng.Offset(0, 1).Value If VBA.Trim(cnum_company) <> "-" And Not dict_cnum_company.Exists(rng.Value & "-" & rng.Offset(0, 1).Value) Then dict_cnum_company.Add rng.Value & "-" & rng.Offset(0, 1).Value, "" End If Next rng 'loop the keys of dict split the keyes by '-' into cnum array and company array. Dim index_dict As Byte Dim arr_cnum() Dim arr_Company() For index_dict = 0 To UBound(dict_cnum_company.keys) ReDim Preserve arr_cnum(1 To UBound(dict_cnum_company.keys) + 1) ReDim Preserve arr_Company(1 To UBound(dict_cnum_company.keys) + 1) arr_cnum(index_dict + 1) = Split(dict_cnum_company.keys()(index_dict), "-")(0) arr_Company(index_dict + 1) = Split(dict_cnum_company.keys()(index_dict), "-")(1) Debug.Print index_dict Next 'assigns the value of the arrays to the celles. sht_out.Range("A1", "A" & UBound(arr_cnum)) = Application.WorksheetFunction.Transpose(arr_cnum) sht_out.Range("B1", "B" & UBound(arr_Company)) = Application.WorksheetFunction.Transpose(arr_Company) 'add 6 columns to output csv file: Dim arr_columns() As Variant arr_columns = Array("C_col", "D_col", "E_col", "F_col", "G_col", "H_col") ' sht_out.Range("C1:H1") = arr_columns Call checkAndCloseWorkbook(str_file_path, False) Call checkAndCloseWorkbook(str_new_file_path, True) Exit Sub error_handling: Call checkAndCloseWorkbook(str_file_path, False) Call checkAndCloseWorkbook(str_new_file_path, False) End Sub ' 辅助函数: 'Get last row of Column N in a Worksheet Function getLastValidRow(in_ws As Worksheet, in_col As String) getLastValidRow = in_ws.Cells(in_ws.Rows.count, in_col).End(xlUp).Row End Function Function checkAndAttachWorkbook(in_wb_path As String) As Workbook Dim wb As Workbook Dim mywb As String mywb = in_wb_path For Each wb In Workbooks If LCase(wb.FullName) = LCase(mywb) Then Set checkAndAttachWorkbook = wb Exit Function End If Next Set wb = Workbooks.Open(in_wb_path, UpdateLinks:=0) Set checkAndAttachWorkbook = wb End Function Function checkAndCloseWorkbook(in_wb_path As String, in_saved As Boolean) Dim wb As Workbook Dim mywb As String mywb = in_wb_path For Each wb In Workbooks If LCase(wb.FullName) = LCase(mywb) Then wb.Close savechanges:=in_saved Exit Function End If Next End Function
三,输出结果:
两种方法输出结果相同:
四,比较总结:
Python pandas 内置了大量处理数据的方法,我们不需要重复造轮子,用起来很方便,代码简洁的多。
Excel VBA 处理这个需求,使用了 数组,字典等数据结构(实际需求中,数据量往往很大,所以一些地方没有直接使用遍历单元格的方法),以及处理字符串,数组和字典的很多方法,对文件的操作也很复杂,一旦出错,调试起来比python也较困难,代码已经尽量优化,但还是远比 Python要多。
到此这篇关于VBA处理数据与Python Pandas处理数据案例比较分析的文章就介绍到这了
原文来自:
本文地址://gulass.cn/vba-python-pandas.html编辑:xiangping wu,审核员:逄增宝
Linux大全:
Linux系统大全: