This is working better so far
This commit is contained in:
=
+102
-103
@@ -22,6 +22,7 @@ import utils.pathfunctions
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import utils.pretty as ct
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import urllib3
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import pandas as pd
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import json
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import ast
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urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
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@@ -52,6 +53,20 @@ def apivalidation():
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case _:
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menu_main()
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def tryToReadCSV(csv):
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try:
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df =pd.read_csv(csv)
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if df.empty:
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print(ct.colorText("Error: CSV file has headers but no data rows.", "red"))
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else:
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print(ct.colorText(f"Data loaded successfully from {csv}", "green"))
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except pd.errors.EmptyDataError:
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print(ct.colorText("Notice : CSV file is completely empty (no headers, no data), falling back to empty frame", "white"))
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df = pd.DataFrame() # Create an empty DataFrame as fallback
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return df
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def menu_main():
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while True:
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print(ct.colorText("\n-----------------------------------", "magenta"))
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@@ -141,53 +156,47 @@ def menu_prepare_to_enforce():
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print(ct.colorText(f" [✓] {first_policy} has been selected as Policy 1","green"))
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print(ct.colorText(f" [✓] {second_policy} has been selected as Policy 2","green"))
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print(ct.colorText("2. Pull and stage event history", "cyan"))
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print(ct.colorText("2. Pulls and stages event history, combines the histories, adds hash info, then categorizes the hashes", "cyan"))
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if os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv") == True:
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print(ct.colorText(f" [✓] This has been completed for {first_policy}","green"))
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elif os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv") == False:
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print(ct.colorText(f" [✗] This step has not been completed","red"))
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elif second_policy is not first_policy and os.path.exists(f"dataframe_csv\\df_aggregated_{second_policy}.csv") == True:
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print(ct.colorText(f" [✓] This has been completed for {second_policy}","green"))
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elif second_policy is not first_policy and os.path.exists(f"dataframe_csv\\df_aggregated_{second_policy}.csv") == False:
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print(ct.colorText(f" [✓] This has not been completed for {second_policy}","red"))
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if os.path.exists(f"dataframe_csv\\executionhist_{first_policy}.csv"):
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print(ct.colorText(f" [✓] Execution history has been compiled for {first_policy}","green"))
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elif not os.path.exists(f"dataframe_csv\\executionhist_{first_policy}.csv"):
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print(ct.colorText(f" [✗] Execution history has not been compiled for {first_policy}","red"))
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elif second_policy is not first_policy and os.path.exists(f"dataframe_csv\\executionhist_{second_policy}.csv"):
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print(ct.colorText(f" [✓] Execution history has been compiled for {second_policy}","green"))
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elif second_policy is not first_policy and not os.path.exists(f"dataframe_csv\\executionhist_{second_policy}.csv"):
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print(ct.colorText(f" [✗] Execution history has not been compiled for {second_policy}","red"))
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print(ct.colorText("3. Combine Staged policies", "cyan"))
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if os.path.exists(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv") == True:
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print(ct.colorText(" [✓] This step has been completed","green"))
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if os.path.exists(f"dataframe_csv\\execuctionhist_combined_{first_policy}_{second_policy}.csv"):
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print(ct.colorText(f" [✓] Execution history has been_combined_for {first_policy} and_{second_policy}", "green"))
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else:
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print(ct.colorText(" [✗] This step has not been completed","red"))
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print(ct.colorText(f" [✗] Execution history has not been_combined_for {first_policy} and_{second_policy}", "red"))
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print(ct.colorText("4. Add hash threat information to list of executions", "cyan"))
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if os.path.exists(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv") == True:
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print(ct.colorText(" [✓] This step has been completed","green"))
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if os.path.exists(f"dataframe_csv\\augmented_combo_{first_policy}_{second_policy}.csv"):
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print(ct.colorText(f" [✓] Hash Info has been added to the combined execution history", "green"))
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else:
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print(ct.colorText(" [✗] This step has not been completed","red"))
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print(ct.colorText(f" [✗] Hash Info has not been added to the combined execution history", "red"))
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print(ct.colorText("5. Categorize your hashes ", "cyan"))
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if os.path.isfile(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv"):
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print(ct.colorText(" [✓] This step has been completed","green"))
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if os.path.exists(f"dataframe_csv\\hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\unapproved_hashes__{first_policy}_{second_policy}.csv"):
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print(ct.colorText(f" [✓] Hashes have been cateogrized", "green"))
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else:
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print(ct.colorText(" [✗] This step has not been completed","red"))
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print(ct.colorText(f" [✗] Hashes have not been cateogrized", "red"))
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print(ct.colorText(f"6. Manually review the files \\dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv and dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", "cyan"))
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print(ct.colorText(f"3. Manually review the files '\\dataframe_csv\\hashes_needing_approval_{first_policy}_{second_policy}.csv' and 'dataframe_csv\\automatically_approved_hashes_{first_policy}_{second_policy}.csv'", "cyan"))
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print(ct.colorText(" Remove the rows containing hashes you do not approve of, and those you would not approve of without metarules.", "cyan"))
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print(ct.colorText(" If metarules need to be created, please make note of them, and remove the row from the csv.", "cyan"))
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print(ct.colorText(" When complete, save both csv files to the directory 'manuallyapproved' and choose this option to combine these approved hashes with the automatically approved hashes and generate a list of paths to be reviewed", "cyan"))
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if os.path.isfile(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
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if os.path.isfile(f"dataframe_csv\\paths_needing_review_{first_policy}_{second_policy}.csv"):
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print(ct.colorText(" [✓] This step has been completed","green"))
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else:
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print(ct.colorText(" [✗] This step has not been completed","red"))
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print(ct.colorText(f"7. Manually review the file df_paths_needing_review_{first_policy}_{second_policy}.csv", "cyan"))
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print(ct.colorText(f"4. Manually review the file 'paths_needing_review_{first_policy}_{second_policy}.csv'", "cyan"))
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print(ct.colorText(" Remove the rows containing path exclusions you do not approve of" , "cyan"))
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print(ct.colorText(" When complete, save the csv file to the directory 'manuallyapproved' and choose this option to generate the preflight lists", "cyan"))
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if os.path.isfile(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile("dataframe_csv\\df_hashdestination_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\df_addtochildpolicy_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\f_addtobaseline_{first_policy}_{second_policy}.csv"):
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if os.path.isfile(f"manuallyapproved\\paths_needing_review_{first_policy}_{second_policy}.csv") and os.path.isfile("dataframe_csv\\hashdestination_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\addtochildpolicy_{first_policy}_{second_policy}.csv") and os.path.isfile(f"dataframe_csv\\addtobaseline_{first_policy}_{second_policy}.csv"):
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print(ct.colorText(" [✓] This step has been completed","green"))
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else:
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print(ct.colorText(" [✗] This step has not been completed","red"))
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@@ -213,83 +222,85 @@ def menu_prepare_to_enforce():
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print(ct.colorText("Please answer with 'yes' or 'no'.", "red"))
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elif choice == "2":
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if not os.path.exists("dataframe_csv\\df_aggregated_{first_policy}.csv"):
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executionhist_policy1 = utils.allowlist.pullPolicyExechistories(url,first_policy_tuple[0], first_policy_tuple[1],True)
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df_aggregated_policy1 = utils.hashfunctions.aggregateHashes(executionhist_policy1)
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df_aggregated_policy1.to_csv(f"dataframe_csv\\df_aggregated_{first_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_policy1, f"dataframe_html\\df_aggregated_{first_policy}.html")
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if not os.path.exists(f"dataframe_csv\\executionhist_{first_policy}.csv"):
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exe1 = utils.allowlist.pullPolicyExechistories(url,first_policy_tuple[0], first_policy_tuple[1],True)
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data = json.loads(exe1)
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executionhist_policy1 = pd.DataFrame(data["response"]["exechistories"])
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executionhist_policy1.to_csv(f"dataframe_csv\\executionhist_{first_policy}.csv", index=False)
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ct.style_dataframe_dark(executionhist_policy1, f"dataframe_html\\executionhist_{first_policy}.html")
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print(ct.colorText(f"Staging of Execution history for policy: {first_policy} is complete","green"))
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if not os.path.exists(f"dataframe_csv\\executionhist_{second_policy}.csv"):
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exe2 = utils.allowlist.pullPolicyExechistories(url,first_policy_tuple[0], first_policy_tuple[1],True)
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data2 = json.loads(exe2)
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executionhist_policy2 = pd.DataFrame(data2["response"]["exechistories"])
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executionhist_policy2.to_csv(f"dataframe_csv\\executionhist_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(executionhist_policy2, f"dataframe_html\\executionhist_{second_policy}.html")
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print(ct.colorText(f"Staging of Exection history for policy: {first_policy} is complete","green"))
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if not os.path.exists("dataframe_csv\\df_aggregated_{second_policy}.csv"):
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executionhist_policy2 = utils.allowlist.pullPolicyExechistories(url,second_policy_tuple[0], second_policy_tuple[1],True)
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df_aggregated_policy2 = utils.hashfunctions.aggregateHashes(executionhist_policy2)
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df_aggregated_policy2.to_csv(f"dataframe_csv\\df_aggregated_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_policy2, f"dataframe_html\\df_aggregated_{second_policy}.html")
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print(ct.colorText(f"Staging of Exection history for policy: {second_policy} is complete","green"))
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#Combine the two policies execution histories
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elif choice == "3":
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if second_policy is first_policy and os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv"):
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df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
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df_aggregated_combo = df1
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df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Dataframes have been aggregated (combined)","green"))
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if second_policy is first_policy:
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execuctionhist_combined = executionhist_policy1
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execuctionhist_combined.to_csv(f"dataframe_csv\\execuctionhist_combined_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\execuctionhist_combined_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Dataframes have been combined","green"))
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elif os.path.exists(f"dataframe_csv\\df_aggregated_{first_policy}.csv") and os.path.exists(f"dataframe_csv\\df_aggregated_{second_policy}.csv"):
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df1 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{first_policy}.csv")
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df2 = tryToReadCSV(f"dataframe_csv\\df_aggregated_{second_policy}.csv")
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df_aggregated_combo = pd.concat([df1 , df2], ignore_index=True)
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df_aggregated_combo.to_csv(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\df_aggregated_combo_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Dataframes have been aggregated (combined)","green"))
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elif os.path.exists(f"dataframe_csv\\executionhist_{first_policy}.csv") and os.path.exists(f"dataframe_csv\\executionhist_{second_policy}.csv"):
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execuctionhist_combined = pd.concat([tryToReadCSV(f"dataframe_csv\\executionhist_{first_policy}.csv") , tryToReadCSV(f"dataframe_csv\\executionhist_{second_policy}.csv")], ignore_index=True)
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execuctionhist_combined.to_csv(f"dataframe_csv\\execuctionhist_combined_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_aggregated_combo, f"dataframe_html\\execuctionhist_combined_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Dataframes have been combined","green"))
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else:
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print(ct.colorText(f"Please stage your data before attempting this step","red"))
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#Keep only unique combinations of hash, filename, and hostname
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if f"dataframe_csv\\execuctionhist_combined_{first_policy}_{second_policy}.csv":
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unique_executions = tryToReadCSV(f"dataframe_csv\\execuctionhist_combined_{first_policy}_{second_policy}.csv").drop_duplicates(subset=['sha256', 'filename', 'hostname'])
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unique_executions.to_csv(f"dataframe_csv\\unique_executions{first_policy}_{second_policy}.csv")
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ct.style_dataframe_dark(unique_executions, f"dataframe_html\\unique_execuctions.html")
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elif choice == "4":
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if os.path.exists(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv"):
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df_augmented = utils.hashfunctions.augmentAggregatedHashes(url,tryToReadCSV(f"dataframe_csv\\df_aggregated_combo_{first_policy}_{second_policy}.csv"))
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df_augmented.to_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_augmented, f"dataframe_html\\df_augmented_combo_{first_policy}_{second_policy}.html")
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#Add Hash info to the combined execution history
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if not os.path.exists(f"dataframe_html\\augmented_combo_{first_policy}_{second_policy}.html"):
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print(ct.colorText(f"Preparing to pull hash info","green"))
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augmented_combo= utils.hashfunctions.augmentAggregatedHashes(url,tryToReadCSV(f"dataframe_csv\\unique_executions{first_policy}_{second_policy}.csv"))
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augmented_combo.to_csv(f"dataframe_csv\\augmented_combo_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(augmented_combo, f"dataframe_html\\augmented_combo_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Hash reputation info added to dataframe","green"))
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#Categorize the hashes
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if os.path.exists(f"dataframe_csv\\hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\automatically_approved_hashes_{first_policy}_{second_policy}.csv") and os.path.exists(f"dataframe_csv\\unapproved_hashes__{first_policy}_{second_policy}.csv"):
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break
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else:
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print(ct.colorText(f"Please combine your data with step 3 prior to attempting this step","red"))
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categorized = utils.hashfunctions.categorizeHashes(pd.read_csv(f"dataframe_csv\\augmented_combo_{first_policy}_{second_policy}.csv"), threat_tolerance_constant, badpublisherlist)
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elif choice == "5":
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if os.path.exists(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"):
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categorized = utils.hashfunctions.categorizeHashes(pd.read_csv(f"dataframe_csv\\df_augmented_combo_{first_policy}_{second_policy}.csv"), threat_tolerance_constant, badpublisherlist)
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categorized[0].to_csv(f"dataframe_csv\\hashes_needing_approval_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[0], f"dataframe_html\\dashes_needing_approval_{first_policy}_{second_policy}.html")
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categorized[0].to_csv(f"dataframe_csv\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[0], f"dataframe_html\\df_hashes_needing_approval_{first_policy}_{second_policy}.html")
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categorized[1].to_csv(f"dataframe_csv\\automatically_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[1], f"dataframe_html\\automatically_approved_hashes_{first_policy}_{second_policy}.html")
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categorized[1].to_csv(f"dataframe_csv\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[1], f"dataframe_html\\df_automatically_approved_hashes_{first_policy}_{second_policy}.html")
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categorized[2].to_csv(f"dataframe_csv\\df_unapproved_hashes__{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[2], f"dataframe_html\\df_unapproved_hashes_{first_policy}_{second_policy}.html")
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categorized[2].to_csv(f"dataframe_csv\\unapproved_hashes__{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(categorized[2], f"dataframe_html\\unapproved_hashes_{first_policy}_{second_policy}.html")
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print(ct.colorText(f"Hashes have been categorized","green"))
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else:
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print(ct.colorText(f"Please Augment your data with hash threat info using step 4 prior to attempting this step","red"))
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elif choice == "6":
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if os.path.exists(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv"):
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df1 = tryToReadCSV(f"manuallyapproved\\df_hashes_needing_approval_{first_policy}_{second_policy}.csv")
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df2 = tryToReadCSV(f"manuallyapproved\\df_automatically_approved_hashes_{first_policy}_{second_policy}.csv")
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elif choice == "3":
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if os.path.exists(f"manuallyapproved\\hashes_needing_approval_{first_policy}_{second_policy}.csv") and os.path.exists(f"manuallyapproved\\automatically_approved_hashes_{first_policy}_{second_policy}.csv"):
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df1 = tryToReadCSV(f"manuallyapproved\\hashes_needing_approval_{first_policy}_{second_policy}.csv")
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df2 = tryToReadCSV(f"manuallyapproved\\automatically_approved_hashes_{first_policy}_{second_policy}.csv")
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df_all_approved_hashes = pd.concat([df1 , df2], ignore_index=True)
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df_all_approved_hashes.to_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_all_approved_hashes, f"dataframe_html\\df_all_approved_hashes_{first_policy}_{second_policy}.html")
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df_all_approved_hashes.to_csv(f"dataframe_csv\\all_approved_hashes_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_all_approved_hashes, f"dataframe_html\\all_approved_hashes_{first_policy}_{second_policy}.html")
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df_paths_needing_review, df_path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_csv(f"dataframe_csv\\df_all_approved_hashes_{first_policy}_{second_policy}.csv"))
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df_paths_needing_review, df_path_ineligible = utils.pathfunctions.filepathInitialGroup(pd.read_csv(f"dataframe_csv\\all_approved_hashes_{first_policy}_{second_policy}.csv"))
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df_paths_needing_review.to_csv(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_paths_needing_review, f"dataframe_html\\df_paths_needing_review_{first_policy}_{second_policy}.html")
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df_paths_needing_review.to_csv(f"dataframe_csv\\paths_needing_review_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_paths_needing_review, f"dataframe_html\\paths_needing_review_{first_policy}_{second_policy}.html")
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df_path_ineligible.to_csv(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv", index=False)
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ct.style_dataframe_dark(df_path_ineligible, f"dataframe_html\\df_path_ineligible_{first_policy}_{second_policy}.html")
|
||||
df_path_ineligible.to_csv(f"dataframe_csv\\path_ineligible_{first_policy}_{second_policy}.csv", index=False)
|
||||
ct.style_dataframe_dark(df_path_ineligible, f"dataframe_html\\path_ineligible_{first_policy}_{second_policy}.html")
|
||||
|
||||
print(ct.colorText(f"Eligible paths determined","green"))
|
||||
|
||||
@@ -297,11 +308,11 @@ def menu_prepare_to_enforce():
|
||||
print(ct.colorText(f"Please manually approve hashes prior to this step","red"))
|
||||
|
||||
|
||||
elif choice == "7":
|
||||
if os.path.exists(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv"):
|
||||
df_approved = tryToReadCSV(f"manuallyapproved\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
|
||||
df_eligible = tryToReadCSV(f"dataframe_csv\\df_paths_needing_review_{first_policy}_{second_policy}.csv")
|
||||
df_ineligible = tryToReadCSV(f"dataframe_csv\\df_path_ineligible_{first_policy}_{second_policy}.csv")
|
||||
elif choice == "4":
|
||||
if os.path.exists(f"manuallyapproved\\paths_needing_review_{first_policy}_{second_policy}.csv"):
|
||||
df_approved = tryToReadCSV(f"manuallyapproved\\paths_needing_review_{first_policy}_{second_policy}.csv")
|
||||
df_eligible = tryToReadCSV(f"dataframe_csv\\paths_needing_review_{first_policy}_{second_policy}.csv")
|
||||
df_ineligible = tryToReadCSV(f"dataframe_csv\\path_ineligible_{first_policy}_{second_policy}.csv")
|
||||
|
||||
approved_set = set([tuple(map(tuple, row)) for row in df_approved.values])
|
||||
|
||||
@@ -315,11 +326,11 @@ def menu_prepare_to_enforce():
|
||||
ct.style_dataframe_dark(df_approved, f"preflight\\Approved_Path_Exclusions_{first_policy}_{second_policy}.html")
|
||||
|
||||
#Seperate out what we arent excluding by path into those that will go into the baseline, and those that will b added to the child.
|
||||
df_addtobaseline = df_ineligible[df_ineligible['reputation status'] == 'KNOWN']
|
||||
df_addtobaseline = df_ineligible[df_ineligible['reputation_status'] == 'KNOWN']
|
||||
df_addtobaseline.to_csv(f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.csv", index=False)
|
||||
ct.style_dataframe_dark(df_addtobaseline, f"preflight\\Add_to_Baseline_{first_policy}_{second_policy}.html")
|
||||
|
||||
df_addtochildpolicy = df_ineligible[df_ineligible['reputation status'] == 'UNKNOWN']
|
||||
df_addtochildpolicy = df_ineligible[df_ineligible['reputation_status'] == 'UNKNOWN']
|
||||
df_addtochildpolicy.to_csv(f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.csv", index=False)
|
||||
ct.style_dataframe_dark(df_addtochildpolicy, f"preflight\\Add_to_Child_Policy_{first_policy}_{second_policy}.html")
|
||||
|
||||
@@ -338,18 +349,6 @@ def menu_prepare_to_enforce():
|
||||
|
||||
|
||||
|
||||
def tryToReadCSV(csv):
|
||||
try:
|
||||
df =pd.read_csv(csv)
|
||||
if df.empty:
|
||||
print(ct.colorText("Error: CSV file has headers but no data rows.", "red"))
|
||||
else:
|
||||
print(ct.colorText("Data loaded successfully.", "green"))
|
||||
except pd.errors.EmptyDataError:
|
||||
print(ct.colorText("Notice : CSV file is completely empty (no headers, no data), falling back to empty frame", "white"))
|
||||
df = pd.DataFrame() # Create an empty DataFrame as fallback
|
||||
return df
|
||||
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
Reference in New Issue
Block a user