From ef4cb038a9ff9b64db9d01f7b6c376ba92028603 Mon Sep 17 00:00:00 2001 From: user_client2024 Date: Mon, 4 Nov 2024 11:34:19 +0000 Subject: [PATCH] System save at 04/11/2024 17:04 by user_client2024 --- .ipynb_checkpoints/main-checkpoint.ipynb | 6 +++--- main.ipynb | 6 +++--- main.py | 6 +++--- 3 files changed, 9 insertions(+), 9 deletions(-) diff --git a/.ipynb_checkpoints/main-checkpoint.ipynb b/.ipynb_checkpoints/main-checkpoint.ipynb index 31ff92b..5c9dde0 100644 --- a/.ipynb_checkpoints/main-checkpoint.ipynb +++ b/.ipynb_checkpoints/main-checkpoint.ipynb @@ -106,9 +106,9 @@ " final_scenario_df = pd.DataFrame(row_list, columns = cols)\n", " final_scenario_df['PARTICIPANT_VOLUME_PCT'] = final_scenario_df['PARTICIPANT_VOLUME']/\\\n", " final_scenario_df['TOTAL_VOLUME'] * 100\n", - " final_scenario_df['Segment'] = 1\n", - " final_scenario_df['SAR_FLAG'] = 1\n", - " final_scenario_df['Risk'] = 1\n", + " final_scenario_df['Segment'] = \"Default\"\n", + " final_scenario_df['SAR_FLAG'] = \"N\"\n", + " final_scenario_df['Risk'] = \"Medium Risk\"\n", " final_scenario_df.dropna(inplace=True)\n", " # final_scenario_df['RUN_DATE'] = final_scenario_df['END_DATE']\n", " return final_scenario_df\n" diff --git a/main.ipynb b/main.ipynb index 31ff92b..5c9dde0 100644 --- a/main.ipynb +++ b/main.ipynb @@ -106,9 +106,9 @@ " final_scenario_df = pd.DataFrame(row_list, columns = cols)\n", " final_scenario_df['PARTICIPANT_VOLUME_PCT'] = final_scenario_df['PARTICIPANT_VOLUME']/\\\n", " final_scenario_df['TOTAL_VOLUME'] * 100\n", - " final_scenario_df['Segment'] = 1\n", - " final_scenario_df['SAR_FLAG'] = 1\n", - " final_scenario_df['Risk'] = 1\n", + " final_scenario_df['Segment'] = \"Default\"\n", + " final_scenario_df['SAR_FLAG'] = \"N\"\n", + " final_scenario_df['Risk'] = \"Medium Risk\"\n", " final_scenario_df.dropna(inplace=True)\n", " # final_scenario_df['RUN_DATE'] = final_scenario_df['END_DATE']\n", " return final_scenario_df\n" diff --git a/main.py b/main.py index f1a001e..6c598cd 100644 --- a/main.py +++ b/main.py @@ -103,9 +103,9 @@ class Scenario: final_scenario_df = pd.DataFrame(row_list, columns = cols) final_scenario_df['PARTICIPANT_VOLUME_PCT'] = final_scenario_df['PARTICIPANT_VOLUME']/\ final_scenario_df['TOTAL_VOLUME'] * 100 - final_scenario_df['Segment'] = 1 - final_scenario_df['SAR_FLAG'] = 1 - final_scenario_df['Risk'] = 1 + final_scenario_df['Segment'] = "Default" + final_scenario_df['SAR_FLAG'] = "N" + final_scenario_df['Risk'] = "Medium Risk" final_scenario_df.dropna(inplace=True) # final_scenario_df['RUN_DATE'] = final_scenario_df['END_DATE'] return final_scenario_df