Upload diamondeconomicdata_159.py

diamondeconomicdata_159.py

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+# -*- coding: utf-8 -*-
+"""DiamondEconomicData.159
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1S_CVJWdykN_6LSpjdHLcSQhC6UVUcFDe
+"""
+
+!pip install ydata-profiling
+
+import pandas as pd
+import numpy as np
+import matplotlib as plt
+import seaborn as sns
+import tensorflow as tf
+from ydata_profiling import ProfileReport
+
+df = pd.read_csv('/content/M6_T2_V1_Diamonds.csv')
+
+df.sample(5)
+
+print(df.head())
+
+df.info()
+
+df.isnull().sum
+
+df.describe()
+
+df.duplicated().sum()
+
+df.head()
+
+df_numeric = df.select_dtypes(include=[np.number])
+df_numeric
+
+df_numeric.corr()['price']
+
+df['cut'].value_counts().plot(kind='bar')
+
+df['color'].value_counts().plot(kind='bar')
+
+df['clarity'].value_counts().plot(kind='bar')
+
+df['cut'].value_counts().plot(kind='pie', autopct='%.2f')
+
+df['color'].value_counts().plot(kind='pie', autopct='%.2f')
+
+df['clarity'].value_counts().plot(kind='pie', autopct='%.2f')
+
+sns.histplot(df['price'])
+
+sns.histplot(df['x'], bins=10)
+
+sns.histplot(df['y'], bins=50)
+
+sns.histplot(df['z'], bins=50)
+
+sns.distplot(df['price'])
+
+sns.distplot(df['x'])
+
+sns.distplot(df['y'])
+
+sns.distplot(df['z'])
+
+sns.boxplot(df['price'])
+
+sns.boxplot(df['x'])
+
+sns.boxplot(df['y'])
+
+sns.boxplot(df['z'])
+
+sns.pairplot(df)
+
+prof = ProfileReport(df)
+prof.to_file(output_file='output.html')
+
+from IPython.core.display import display, HTML
+
+with open('/content/output.html', 'r') as file:
+  html_content = file.read()
+
+display(HTML(html_content))
+