banking_breakdown/__main__.py

@@ -1,9 +1,34 @@
+import pandas as pd
 from banking_breakdown import document_builder
-from banking_breakdown import statement_parser
+import subprocess
+import os
+import shutil
+
+import pandas as pd
+
+from banking_breakdown import types
+import numpy as np
 
 
 def main():
-    report_data = statement_parser.parse_statement("res/banking_statement_2023.csv")
+    categories = ["A", "B", "C", "D", "E", "F", "G"]
+    values = np.array([10, 12, 53, 12, 90, 23, 32])
+    values = values / values.sum() * 100
+
+    total_value = np.random.normal(size=10) + 4
+    net_income = np.diff(total_value)
+
+    category_overview_df = pd.DataFrame(
+        {"category": categories, "value": values.astype('int32')})
+    t = np.linspace(0, total_value.size, total_value.size)
+    total_value_df = pd.DataFrame({"t": t, "value": total_value})
+    t = np.linspace(0, net_income.size, net_income.size)
+    net_income_df = pd.DataFrame({"t": t, "value": net_income})
+
+    report_data = types.ReportData(category_overview=category_overview_df,
+                                   net_income=net_income_df,
+                                   total_value=total_value_df)
+
     document_builder.build_document(report_data)
 
 

banking_breakdown/document_builder.py

@@ -15,8 +15,6 @@ def _serialize_report_data(report_data: types.ReportData):
     report_data.category_overview.to_csv('build/category_overview.csv',
                                          index=False)
     report_data.total_value.to_csv('build/total_value.csv', index=False)
-    report_data.detailed_balance.to_csv('build/detailed_balance.csv',
-                                        index=False)
 
 
 def _compile_document():

banking_breakdown/statement_parser.py

@@ -1,80 +0,0 @@
-import typing
-import pandas as pd
-from banking_breakdown import types
-import json
-import re
-import numpy as np
-
-
-def _read_regex_dict(regex_file: str = "res/category_regexes.json"):
-    with open(regex_file, 'r') as f:
-        return json.load(f)
-
-
-def _tag_with_category(df: pd.DataFrame) -> pd.DataFrame:
-    regex_dict = _read_regex_dict()
-
-    return df
-
-
-def _compute_total_balance(df: pd.DataFrame) -> pd.DataFrame:
-    stripped_df = pd.DataFrame(
-        {'t': df["Buchungstag"], 'value': df["Saldo nach Buchung"]})
-
-    stripped_df.index = stripped_df['t']
-    gb = stripped_df.groupby(pd.Grouper(freq='M'))
-
-    result = gb.tail(1)['value'].reset_index()
-    #result['t'] = result['t'].apply(lambda dt: dt.replace(day=1))
-
-    return result
-
-
-def _compute_net_income(df: pd.DataFrame) -> pd.DataFrame:
-    stripped_df = pd.DataFrame({'t': df["Buchungstag"], 'value': df["Betrag"]})
-
-    result = stripped_df.resample(rule='M', on="t").sum().reset_index()
-    #result['t'] = result['t'].apply(lambda dt: dt.replace(day=1))
-
-    return result
-
-
-def _compute_category_overview(df: pd.DataFrame) -> pd.DataFrame:
-    categories = ["A", "B", "C", "D", "E", "F", "G"]
-    values = np.array([10, 12, 53, 12, 90, 23, 32])
-    values = values / values.sum() * 100
-    values = np.round(values, decimals=1)
-    values[-1] += 100 - np.sum(values)
-
-    category_overview_df = pd.DataFrame(
-        {"category": categories, "value": values})
-
-    return category_overview_df
-
-
-def _compute_detailed_balance(df: pd.DataFrame) -> pd.DataFrame:
-    return pd.DataFrame({'t': df["Buchungstag"],
-                         'value': df["Saldo nach Buchung"]})
-
-
-def parse_statement(filename: str) -> types.ReportData:
-    df = pd.read_csv(filename, delimiter=';', decimal=",")
-    df["Buchungstag"] = pd.to_datetime(df["Buchungstag"], format='%d.%m.%Y')
-
-    category_overview_df = _compute_category_overview(df)
-    total_balance_df = _compute_total_balance(df)
-    net_income_df = _compute_net_income(df)
-    detailed_balance_df = _compute_detailed_balance(df)
-
-    return types.ReportData(category_overview_df,
-                            net_income_df,
-                            total_balance_df,
-                            detailed_balance_df)
-
-
-def main():
-    report_data = parse_statement("../res/banking_statement_2023.csv")
-
-
-if __name__ == "__main__":
-    main()

banking_breakdown/types.py

@@ -7,4 +7,3 @@ class ReportData:
     category_overview: pd.DataFrame
     net_income: pd.DataFrame
     total_value: pd.DataFrame
-    detailed_balance: pd.DataFrame

res/report.tex

@@ -4,7 +4,6 @@
 \usepackage{amsmath}
 \usepackage{pgfplots}
 \pgfplotsset{compat=newest}
-\usetikzlibrary{pgfplots.dateplot}
 
 % Other packages
 \usepackage[a4paper, total={12cm, 25cm}]{geometry}
@@ -31,10 +30,6 @@
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 
-\makeatletter
-\newcommand*\shortyear[1]{\expandafter\@gobbletwo\number\numexpr#1\relax}
-\makeatother
-
 \newcommand{\slice}[6]{
 	\pgfmathparse{0.5*#1+0.5*#2}
 	\let\midangle\pgfmathresult
@@ -141,34 +136,15 @@
 
 		\begin{tikzpicture}
 			\begin{axis}[
-				date coordinates in=x,
 				width=\textwidth,
 				height=0.375\textwidth,
 				ylabel={Net income in €},
 				y label style={at={(-0.1,0.5)},anchor=south},
-				xticklabel=\month.\shortyear{\year},
-				xtick=data,
-				xticklabel style={
-					rotate=60,
-					anchor=near xticklabel,
-				},
-				grid,
-				enlarge x limits=0.03,
 			]
-				% Dummy plot to set x axis ticks
+				\addplot+[ybar, color=scol2, fill=scol2, line width=1pt]
-				\addplot[draw=none]
-					table[col sep=comma, x=t, y=value]
-						{net_income.csv};
-
-				% Dummy plot to set x axis scale
-				\addplot[draw=none]
-					table[col sep=comma, x=t, y=value]
-						{detailed_balance.csv};
-
-				\addplot[ybar, color=scol2, fill=scol2, line width=1pt]
 					table[col sep=comma, x=t, y=value, discard if lt={value}{0}]
 						{net_income.csv};
-				\addplot[ybar, color=scol0, fill=scol0, line width=1pt]
+				\addplot+[ybar, color=scol0, fill=scol0, line width=1pt]
 					table[col sep=comma, x=t, y=value, discard if gt={value}{0}]
 						{net_income.csv};
 			\end{axis}
@@ -179,31 +155,15 @@
 
 		\begin{tikzpicture}
 			\begin{axis}[
-				date coordinates in=x,
 				width=\textwidth,
 				height=0.375\textwidth,
+				area style,
 				ylabel={Total balance in €},
 				y label style={at={(-0.1,0.5)},anchor=south},
-				xticklabel=\month.\shortyear{\year},
-				xtick=data,
-				enlarge x limits=0.03,
-				xticklabel style={
-					rotate=60,
-					anchor=near xticklabel,
-				},
-				grid,
 			]
-				% Dummy plot to set x axis ticks
+				\addplot+[mark=none, color=scol1, line width=1pt]
-				\addplot[draw=none]
 					table[col sep=comma, x=t, y=value]
-						{total_value.csv};
+						{total_value.csv} \closedcycle;
-
-				\addplot[scol3, mark=none, line width=1pt]
-					table[col sep=comma, x=t, y=value]
-						{detailed_balance.csv};
-				\addplot[scol1, mark=none, line width=1pt]
-					table[col sep=comma, x=t, y=value]
-						{total_value.csv};
 			\end{axis}
 		\end{tikzpicture}
 	\end{subfigure}
@@ -211,6 +171,5 @@
 	\caption{Development of account balance over time}
 \end{figure}
 
-
 \end{document}