Generate the transaction flow over time graphs

bankView.py

@@ -1,9 +1,13 @@
 #BankView - Calculate and Build Banking Stats
 #Cal.W 2020
 
-import csv, statistics
+import csv, statistics, os
 from datetime import datetime
 
+import matplotlib
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+
 TRANSACTION_TYPES = ['Other', "Tap and Pay", "Card", "Deposit"]
 
 #transDetails, transDate, transType, transAcc
@@ -116,6 +120,28 @@ def saveTransactionData(transactions, fileName="transData.csv"):
     
     return
 
+
+#Load and if found update the transaction db
+def loadUpdateTransactionData(dbFileName="transData.csv", importFileName="import.csv", mvImportFileName=None):
+    if mvImportFileName is None: mvImportFileName = './imported_'+datetime.now().strftime("%Y-%m-%d")+'.csv'
+
+    trans = list()
+    if(os.path.isfile(dbFileName)):
+        trans = loadTransactionData(dbFileName)
+
+    if (os.path.isfile(importFileName)):
+        trans = importTransactionData(importFileName, transactions=trans)
+        os.rename(importFileName, mvImportFileName)
+        saveTransactionData(trans)
+
+    if len(trans) < 1:
+        raise ImportError("No transactions to use!")
+
+    return trans
+
+
+
+
 def calculateStats(transactions, yearRangeVal=None, monthRangeVal=None, otherFelid=None):
     yearRange = lambda x: True
     if isinstance(yearRangeVal, type(yearRange)): yearRange = yearRangeVal
@@ -145,7 +171,42 @@ def calculateStats(transactions, yearRangeVal=None, monthRangeVal=None, otherFel
         "lowestBalance"  : float(min(periodTransactions, key=lambda x: x[4])[4])                           if len(periodTransactions) > 0 else float(0),
     }
 
-    return stats
+    return stats, periodTransactions
+
+
+def drawTransactionGraphs(trans):
+    stats, statTrans = calculateStats(trans)
+
+    fig, ax = plt.subplots(2, sharex=True)
+    #ax[0].xaxis.set_major_formatter(mdates.DateFormatter('%m/%Y'))
+    #ax[0].xaxis.set_major_locator(mdates.DayLocator(interval=60))
+    ax[0].fmt_xdata = mdates.DateFormatter('%Y-%m-%d')
+    ax[0].plot([x[1].date() for x in statTrans], [x[4] for x in statTrans])
+    ax[0].set(title='Transaction History')
+    ax[0].tick_params(
+        axis='x',          # changes apply to the x-axis
+        which='both',      # both major and minor ticks are affected
+        bottom=False,      # ticks along the bottom edge are off
+        top=False,         # ticks along the top edge are off
+        labelbottom=False  # labels along the bottom edge are off
+    )
+    ax[0].grid()
+    
+
+    #ax[1].xaxis.set_major_formatter(mdates.DateFormatter('%m/%Y'))
+    #ax[1].xaxis.set_major_locator(mdates.DayLocator())
+    ax[1].fmt_xdata = mdates.DateFormatter('%Y-%m-%d')
+    ax[1].plot([x[1].date() for x in statTrans], [x[2] for x in statTrans])
+    ax[1].set(title='Transaction Amounts Over Time')
+    ax[1].grid()
+    
+    fig.tight_layout()
+    fig.autofmt_xdate()
+
+    fig.text(0.5, 0.05, 'Date (Month/Year)', ha='center')
+    fig.text(0.015, 0.5, 'Transaction Amount ($)', va='center', rotation='vertical')
+    #fig.savefig("test.png")
+    plt.show()
 
 
 def foo(transactions):
@@ -157,18 +218,9 @@ def foo(transactions):
     for year in years:
         pass
 
-import pprint
-
-#[TODO] Net balance and averages seem funny / dont line up with excell :/
 
 if __name__ == "__main__":
-    trans = loadTransactionData()
-    y = lambda x: x[-2] == TRANSACTION_TYPES[1]
-    stats = calculateStats(trans, 2020, 1, y) 
-    pprint.pprint(stats, indent=4)
-    
-    #calculateStats(trans)
-    
-    
-    
-    #[print(x) for x in trans if x[-2] == TRANSACTION_TYPES[-1]]
+    trans = loadUpdateTransactionData()
+
+    drawTransactionGraphs(trans)
+