From 3b668fad5ef2d9ad94729b9d3b81eeda1659a486 Mon Sep 17 00:00:00 2001
From: Lea Kyveli Chrysanthopoulou <leacty3@gmail.com>
Date: Fri, 14 Apr 2023 23:04:05 +0200
Subject: [PATCH] Add p_values
---
delta_measure.py | 8 ++++++++
1 file changed, 8 insertions(+)
diff --git a/delta_measure.py b/delta_measure.py
index 4d2025d..84bb84a 100644
--- a/delta_measure.py
+++ b/delta_measure.py
@@ -5,6 +5,7 @@ import pandas as pd
import statistics
import re
import dataframe_image as dfi
+import scipy.stats
data_overview = pd.DataFrame(pd.read_csv("data_overview/data_overview.csv", index_col=0))
@@ -27,6 +28,9 @@ mean_std_dev_list = [[columnName, columnData.mean(), columnData.std()] for colum
# Create a new DataFrame with the same column names and index labels as data_overview
z_scores_all_data = pd.DataFrame(columns=data_overview.columns, index=data_overview.index)
+p_values_all_data = pd.DataFrame(columns=data_overview.columns, index=data_overview.index)
+
+
# Iterate over each cell in the data_overview DataFrame and write the corresponding z-score in the z_scores_all_data DataFrame
for index, row in data_overview.iterrows():
for column in data_overview.columns:
@@ -34,8 +38,12 @@ for index, row in data_overview.iterrows():
cell_value = data_overview.loc[index, column]
z_score = (cell_value - mean) / std_dev
z_scores_all_data.loc[index, column] = z_score
+ p_value = scipy.stats.norm.sf(abs(z_score))
+ p_values_all_data[index, column] = p_value
+
dfi.export(z_scores_all_data, "data_overview/z_scores_all_data.png", table_conversion = "matplotlib")
+dfi.export(p_values_all_data, "data_overview/p_values_all_data.png", table_conversion = "matplotlib")
print(z_scores_all_data)
--
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