Upload 1259_249_252.py

1259_249_252.py

@@ -0,0 +1,47 @@
+# -*- coding: utf-8 -*-
+"""1259_249_252
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1vs6TIReUJQaUJVTdrxZZRWWFH9nbbMvu
+"""
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+import seaborn as sns
+
+import os
+for dirname, _, filenames in os.walk('/content/enhanced_student_habits_performance_dataset.csv'):
+  for filename in filenames:
+    print(os.path.join(dirname, filename))
+
+df=pd.read_csv('/content/enhanced_student_habits_performance_dataset.csv')
+
+df.info()
+
+df.isnull().sum()
+
+num_col=df.select_dtypes(exclude='object')
+cat_col=df.select_dtypes(include='object')
+num_col.drop(columns=['student_id'], inplace=True)
+
+fig, ax=plt.subplots(3,6,figsize=(20, 10))
+ax=ax.flatten()
+for i, col in enumerate(num_col.columns):
+  sns.histplot(kde=True, x=df[col], ax=ax[i])
+  plt.title(f'Distribution of {col}')
+
+df['exam_anxiety_score'].value_counts()
+print('These students have outrageous exam anxiety score:', end='')
+print((df[df['exam_anxiety_score']==10].shape[0]/df.shape[0])*100)
+
+anx=df[df['exam_anxiety_score']==10]
+num_col_anx=anx.select_dtypes(exclude='object')
+num_col_anx.drop(columns=['student_id'], inplace=True)
+fig, ax=plt.subplots(3,6, figsize=(20,10))
+ax=ax.flatten()
+for i, col in enumerate(num_col_anx.columns):
+  sns.histplot(kde=True, x=num_col_anx[col],ax=ax[i])
+  plt.title(f' Distributoin of {col}')