Question

import easygui as gui
import pandas as pd
filename = gui.fileopenbox(msg='Please choose the Excel workbook containing the bank data.') #select workbook containing FC and WF data
colnames=['1','2','3','4','5','6','7','8','9','10','11','12'] #define col names because variable number of col won't read unless max col# is defined
dfdata = pd.read_csv(filename,names=colnames) #set dataframe equal to csv file
key = dfdata["12"].isnull() #set criteria for splitting data equal to null value in column 12
dftopdata = dfdata.loc[key] #set new df equal to key criteria
dfbottomdata = dfdata.loc[~key] #set new df NOT equal to key criteria
dftopdata = dftopdata.dropna(axis=1, how='all', thresh=None, subset=None) #drop any column with all values = NaN
dftopdata = dftopdata.dropna(axis=0, how='all', thresh=None, subset=None) #drop any row with all values = NaN
header = dftopdata.iloc[1] #Creates a header variable at row index location 1
dftopdata = dftopdata[2:] #Resets dataframe equal to row 2 and beyond
dftopdata.rename(columns = header, inplace = True) #sets names of columns in the dataframe equal to header
header = dfbottomdata.iloc[0] #Creates a header variable at row index location 0
dfbottomdata = dfbottomdata[1:] #Resets dataframe equal to row 1 and beyond
dfbottomdata.rename(columns = header, inplace = True) #sets names of columns in the dataframe equal to header

上面的代码导致两个数据帧。

这是来自数据帧的数据样本，称为顶部数据：

Routing        Currency  Account Number  Account Name  Opening Ledger  Credits Amt  Credits Num  Debits Amt  Debits Num  Closing Ledger 
123456789      USD       1111111112      A             717.57          100.00       1            100.72      3           716.85         
123456789      USD       1111111113      B             1,350.30        NaN          0            28.53       1           1,321.77       
123456789      USD       1111111114      C             26,570.34       320.52       1            42.17       1           26,848.69      
123456789      USD       1111111115      D             1,031.95        2,000.00     1            703.95      2           2,328.00       
123456789      USD       1111111116      E             1,000.00        600.00       2            72.03       2           1,527.97

这是来自数据帧的数据样本，称为底部数据：

Date        Routing        Currency  Account Number  Account Name  BAI Type            BAI Code  CR Amount  DB Amount  Serial Num  Ref Num   Description                                       
12/10/2019  123456789      USD       1111111112      A             Miscellaneous Fees  7         NaN        28.69      NaN         69650977  MTHLY ANALYSIS CHARGE                             
12/20/2019  123456789      USD       1111111112      A             Misc Credit         1         100        NaN        NaN         70069250  XFR TO DDA FR DDA 001111085716122019RF#1452300... 
12/24/2019  123456789      USD       1111111112      A             Misc Debit          4         NaN        69.08      NaN         70184768  ACCESSIBLEINSURA WEBPAYMENTPCOF PROPERTIES SERIES 
12/24/2019  123456789      USD       1111111112      A             Misc Debit          5         NaN        2.95       NaN         70184769  SEP INSURANC ACH WEBPAYMENTPCOF PROPERTIES SERIES 
12/10/2019  123456789      USD       1111111113      B             Miscellaneous Fees  6         NaN        28.53      NaN         69645166  MTHLY ANALYSIS CHARGE

我想在底部数据df中添加一个名为“余额”的新列，该列包含每个银行帐户的余额。

底部数据df中给定银行帐户最早交易日期的余额应等于该银行帐户在第一个数据框中的期初分类账值加上底部的该行中的任何贷项或减去任何借项数据df。

给定银行帐户的每个后续交易应等于前一个交易日期以来的余额加上底数df的该行中的任何贷方或减去任何借方。

这就是我希望底层数据df在分析后的样子：

    Date        Routing        Currency  Account Number  Account Name  BAI Type            BAI Code  CR Amount  DB Amount  Serial Num  Ref Num   Description                                        Balance           
    12/10/2019  123456789      USD       1111111112      A             Miscellaneous Fees  7         NaN        28.69      NaN         69650977  MTHLY ANALYSIS CHARGE                              688.88            
    12/20/2019  123456789      USD       1111111112      A             Misc Credit         1         100        NaN        NaN         70069250  XFR TO DDA FR DDA 001111085716122019RF#1452300...  788.88            
    12/24/2019  123456789      USD       1111111112      A             Misc Debit          4         NaN        69.08      NaN         70184768  ACCESSIBLEINSURA WEBPAYMENTPCOF PROPERTIES SERIES  719.80            
    12/24/2019  123456789      USD       1111111112      A             Misc Debit          5         NaN        2.95       NaN         70184769  SEP INSURANC ACH WEBPAYMENTPCOF PROPERTIES SERIES  716.85            
    12/10/2019  123456789      USD       1111111113      B             Miscellaneous Fees  6         NaN        28.53      NaN         69645166  MTHLY ANALYSIS CHARGE                              1321.77

但是我对下一步的工作感到困惑。

我已经考虑过为每个银行帐户创建一个数据框，但这似乎效率很低。

有人可以指出我正确的方向吗？

Answer 1

假设dfbottomdata对Date，Routing和Account Number的值升序排列（从最小到最大），则下面的代码应该起作用：

#Add Closing Ledger value from dftopdata
dfbottomdata = dfbottomdata.merge(dftopdata[['Routing','Account Number','Opening Ledger']], on=['Routing','Account Number'])
dfbottomdata.rename(columns={'Opening Ledger': 'Balance'}, inplace=True)

#Replace NaN with 0 for calculations
dfbottomdata['CR Amount'].fillna(0, inplace=True)
dfbottomdata['DB Amount'].fillna(0, inplace=True)

#Handle use case for first row
dfbottomdata.loc[0, 'Balance'] = dfbottomdata.loc[0, 'Balance'] + dfbottomdata.loc[0, 'CR Amount'] - dfbottomdata.loc[0, 'DB Amount']

#Iterate through each row, applying logic only if previous row Routing/AccountNumber match
for i in range(1, len(dfbottomdata)):
    if (dfbottomdata.loc[i-1, 'Routing'] == dfbottomdata.loc[i, 'Routing']) & (dfbottomdata.loc[i-1, 'Account Number'] == dfbottomdata.loc[i, 'Account Number']):
        dfbottomdata.loc[i, 'Balance'] = dfbottomdata.loc[i-1, 'Balance'] + dfbottomdata.loc[i, 'CR Amount'] - dfbottomdata.loc[i, 'DB Amount']
    else:
        dfbottomdata.loc[i, 'Balance'] = dfbottomdata.loc[i, 'Balance'] + dfbottomdata.loc[i, 'CR Amount'] - dfbottomdata.loc[i, 'DB Amount']

如何根据条件过滤后的熊猫数据框来导出列

1 个答案: