Coders Packet

Clothe Size Analyzing using Python in Machine Learning

By Subhojit Jalal

  • Clothe.csv
  • CLOTHE SIZE.ipynb
  • In this project, we analyze the clothing size, plot a graph between sizes and count and also plot heatmap using Python in Machine Learning.

    Step:- 1

    First, we upload the necessary libraries then we upload the dataset

    import pandas as pd
    import numpy as np
    import seaborn as sns
    import matplotlib.pyplot as plt
    CLL = pd.read_csv("Clothe.csv")
    CLL
    CLL.isna().sum()
    CLL.describe()
    CLL.info()
    CLL['age'] = CLL['age'].fillna(CLL['age'].median())
    CLL['height'] = CLL['height'].fillna(CLL['height'].median(
    CLL.isna().sum()

    Step:- 2

    Now Plotting histogram between Count and Predictor

    fig, axes = plt.subplots(1,3,figsize=(20,5))
    fig.suptitle('Predictor')
    
    # weight
    sns.histplot(CLL['weight'], ax = axes[0])
    axes[0].set_title('weight')
    
    # age
    sns.histplot(CLL['age'], ax = axes[1])
    axes[1].set_title('age')
    
    # height
    sns.histplot(CLL['height'], ax = axes[2])
    axes[2].set_title('height')

    Now Plotting histogram between Weight and Predictor

    fig, axes = plt.subplots(1,3,figsize=(20,5))
    fig.suptitle('Predictor')
    
    # weight
    sns.boxplot(x = 'size',y = 'weight', data = CLL, ax = axes[0])
    axes[0].set_title('weight')
    
    # age
    sns.boxplot(x = 'size',y = 'age', data = CLL, ax = axes[1])
    axes[1].set_title('age')
    
    # height
    sns.boxplot(x = 'size',y = 'height', data = CLL, ax = axes[2])
    axes[2].set_title('height')

    Step:- 3

     

    CLL['size'].value_counts()

    Here we see the most numbers of people use "M" Size and fewer numbers of people use "XXL"

    sns.countplot(x = 'size', data = CLL)

    Plotting graph between count and size

    CLL['size'] = CLL['size'].map({"XXS": 1,
                                 "S": 2,
                                 "M" : 3,
                                 "L" : 4,
                                 "XL" : 5,
                                 "XXL" : 6,
                                 "XXXL" : 7})
    CLL.head()

    Mapping clothes size from strings to numeric

    sns.heatmap(CLL.corr(), annot=True)

    Now we Plot a heat map

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