Removing TODOs, reading data from the web, updating code to remove warnings

Author: gusamarante

example_br.py

@@ -8,13 +8,13 @@
 
 # Read and plot data
 yield_curve = pd.read_csv(
-    "sample_data/di monthly maturities.csv",  # TODO change to read from web
+    "https://raw.githubusercontent.com/gusamarante/pyacm/refs/heads/main/sample_data/di%20monthly%20maturities.csv",
     index_col=0,
 )
 yield_curve = yield_curve.iloc[:, :121]  # maturities up to 10y
 yield_curve = yield_curve.dropna()
 yield_curve.index = pd.to_datetime(yield_curve.index)
-yield_curve = yield_curve[yield_curve.index >= "2007-03-01"]  # TODO deal with this missing data
+yield_curve = yield_curve[yield_curve.index >= "2007-03-01"]
 
 
 # Plot the Series of selcted maturities

example_us.py

@@ -19,7 +19,7 @@
 yield_curve = yield_curve.iloc[:, :121]  # maturities up to 10y
 yield_curve = yield_curve.dropna()
 yield_curve.index = pd.to_datetime(yield_curve.index)
-yield_curve = yield_curve[yield_curve.index >= "2007-03-01"]  # TODO deal with this missing data
+yield_curve = yield_curve[yield_curve.index >= "2007-03-01"]
 
 tp = pd.DataFrame(columns=yield_curve.columns)
 er = pd.DataFrame(columns=yield_curve.columns)

pit_estimates.py

@@ -130,7 +130,7 @@ def __init__(self, curve, n_factors=5):
 
         self.n_factors = n_factors
         self.curve = curve
-        self.curve_monthly = curve.resample('M').mean()
+        self.curve_monthly = curve.resample('ME').mean()
         self.t = self.curve_monthly.shape[0] - 1
         self.n = self.curve_monthly.shape[1]
         self.rx_m, self.rf_m = self._get_excess_returns()

pyacm/acm.py

@@ -92,9 +92,9 @@ def _fetch_single_code(series_id):
 
         url = r'https://fred.stlouisfed.org/data/' + series_id + '.txt'
         df = pd.read_csv(url, sep='\t')
-        series_start = df[df[df.columns[0]].str.contains('DATE\s+VALUE')].index[0] + 1
+        series_start = df[df[df.columns[0]].str.contains(r'DATE\s+VALUE')].index[0] + 1
         df = df.loc[series_start:]
-        df = df[df.columns[0]].str.split('\s+', expand=True)
+        df = df[df.columns[0]].str.split(r'\s+', expand=True)
         df = df[~(df[1] == '.')]
         df = pd.DataFrame(data=df[1].values.astype(float),
                           index=pd.to_datetime(df[0]),