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我已經構建了一個程序,用於執行一些數據分析,然後將其保存爲我的桌面上的CSV。Python Pandas - 創建CSV並添加數據,而不是保存它
問題是,我的桌面的路徑有我的名字,我不會知道任何其他人使用它的路徑(即它不會工作)。
有沒有辦法打開一個新的CSV並將數據插入(並讓它們保存),而不是程序保存它?
我的代碼是:
import pandas as pd
import pyodbc
d=[]
key1 = raw_input('enter a keyword to search for: ')
key2 = raw_input('enter another keyword to search for: ')
conn = pyodbc.connect('DSN=QueryBuilder')
cursor = conn.cursor()
stringQ ="SELECT GrantInformation.GrantRefNumber, GrantInformation.PIName, GrantInformation.Call, GrantInformation.RoutingClassification, GrantInformation.GrantCategory, GrantInformation.AuthorisationDate, GrantInformation.HoldingOrganisationName, GrantInformation.StatusGeneral, GrantInformation.GrantTitle, GrantSummary.Summary, GrantDates.ActualStartDate, GrantDates.ActualEndDate, GrantInformation.TotalGrantValue FROM (GrantInformation LEFT JOIN GrantSummary ON GrantInformation.GrantRefNumber = GrantSummary.GrantRefNumber) LEFT JOIN GrantDates ON GrantInformation.GrantRefNumber = GrantDates.GrantRefNumber WHERE (((GrantInformation.AuthorisationDate)>='2005/4/1') AND ((GrantInformation.StatusGeneral) Like '%auth%') AND ((GrantInformation.GrantTitle) Like '%{}%'AND (GrantInformation.TransferInd)= 'false' OR (GrantInformation.GrantTitle) Like '%{}%') AND ((GrantInformation.TransferInd)= 'false')) OR (((GrantInformation.AuthorisationDate)>='2005/4/1') AND ((GrantInformation.StatusGeneral) Like '%auth%') AND ((GrantSummary.Summary) Like '%{}%'AND (GrantInformation.TransferInd)= 'false' OR (GrantSummary.Summary) Like '%{}%' AND (GrantInformation.TransferInd)= 'false'));".format(key1,key2,key1,key2)
cursor.execute(stringQ)
rows = cursor.fetchall()
for row in rows:
d.append({'GrantRefNumber':row[0],'Call':row[2],'Classification':row[3],'Grant Category':row[4],'Authorisation Date':row[5],'Organisation':row[6],'Status General':row[7],'Grant Title':row[8],'Summary':row[9],'Start Date':row[10],'End Date':row[11],'Total Value':row[12]})
df = pd.DataFrame(d)
new_df = df[['GrantRefNumber','Grant Title','Organisation','Call','Grant Category','Authorisation Date','Status General','Total Value','Classification','Start Date','End Date','Summary']]
new_df.to_csv("C:/Users/nicholas/Desktop/data.csv", header=True, index=False, encoding='utf-8')
Awesom e,謝謝你! :)......沒有意識到這很簡單 – ScoutEU