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