diff --git a/MISOReports/parsers.py b/MISOReports/parsers.py
index eed29d6..22be909 100644
--- a/MISOReports/parsers.py
+++ b/MISOReports/parsers.py
@@ -2537,12 +2537,128 @@ def parse_RT_LMPs(
 def parse_sr_gfm(
     res: requests.Response,
 ) -> pd.DataFrame:
-    df = pd.read_excel(
+    MarketHourColumn = pd.read_excel(
         io=io.BytesIO(res.content),
-        skiprows=3,
+        skiprows=4,
+        usecols="A",
+    )[:-1]
+
+    MarketHourColumn["Market Hour Ending"] = MarketHourColumn["Market Hour Ending"].astype(pandas.core.arrays.string_.StringDtype())
+
+    df1 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="B:J",
+        sheet_name="RT Generation Fuel Mix",
     )[:-1]
+    shared_column_names = list(df1.columns)[:-2]
+
+    df1[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]] = df1[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]].astype(numpy.dtypes.Float64DType())
     
-    raise NotImplementedError("Parsing of this report is not yet implemented.")
+    df2 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="L:T",
+        sheet_name="RT Generation Fuel Mix",
+        names=shared_column_names + ["Storage", "Total MW"],
+    )[:-1]
+
+    df2[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]] = df2[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]].astype(numpy.dtypes.Float64DType())
+
+    df3 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="V:AC",
+        sheet_name="RT Generation Fuel Mix",
+        names=shared_column_names + ["Total MW"],
+    )[:-1]
+
+    df3[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Total MW"]] = df3[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Total MW"]].astype(numpy.dtypes.Float64DType())
+
+    df4 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="AG:AO",
+        sheet_name="RT Generation Fuel Mix",
+        names=shared_column_names + ["Storage", "MISO"],
+    )[:-1]
+
+    df4[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "MISO"]] = df4[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "MISO"]].astype(numpy.dtypes.Float64DType())
+
+    df5 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="B:J",
+        sheet_name="DA Cleared Generation Fuel Mix",
+        names=shared_column_names + ["Storage", "Total MW"],
+    )[:-1]
+
+    df5[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]] = df5[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]].astype(numpy.dtypes.Float64DType())
+
+    df6 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="L:T",
+        sheet_name="DA Cleared Generation Fuel Mix",
+        names=shared_column_names + ["Storage", "Total MW"],
+    )[:-1]
+
+    df6[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]] = df6[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "Total MW"]].astype(numpy.dtypes.Float64DType())
+
+    df7 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="V:AC",
+        sheet_name="DA Cleared Generation Fuel Mix",
+        names=shared_column_names + ["Total MW"],
+    )[:-1]
+
+    df7[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Total MW"]] = df7[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Total MW"]].astype(numpy.dtypes.Float64DType())
+
+    df8 = pd.read_excel(
+        io=io.BytesIO(res.content),
+        skiprows=4,
+        usecols="AG:AO",
+        sheet_name="DA Cleared Generation Fuel Mix",
+        names=shared_column_names + ["Storage", "MISO"],
+    )[:-1]
+
+    df8[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "MISO"]] = df8[["Coal", "Gas", "Nuclear", "Hydro", "Wind", "Solar", "Other", "Storage", "MISO"]].astype(numpy.dtypes.Float64DType())
+
+
+    df_list = [df1, df2, df3, df4, df5, df6, df7, df8]
+
+    for df in df_list:
+        df.insert(
+            loc=0,
+            column="Market Hour Ending",
+            value=MarketHourColumn["Market Hour Ending"],
+        )
+
+    df = pd.DataFrame({
+        MULTI_DF_NAMES_COLUMN: [
+                "RT Generation Fuel Mix Central",
+                "RT Generation Fuel Mix North",
+                "RT Generation Fuel Mix South",
+                "RT Generation Fuel Mix Totals",
+                "DA Cleared Generation Fuel Mix Central",
+                "DA Cleared Generation Fuel Mix North",
+                "DA Cleared Generation Fuel Mix South",
+                "DA Cleared Generation Fuel Mix Totals",
+        ], 
+        MULTI_DF_DFS_COLUMN: [
+                df1, 
+                df2,
+                df3,
+                df4,
+                df5,
+                df6,
+                df7,
+                df8,
+        ],
+    })
+
+    return df
 
 
 def parse_dfal_HIST(