Diwali_slale

import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns dataframe = pd.read_csv("Zomato data.csv", delimiter=",") # Ensure delimiter is correct print("First 5 rows of the dataset:") print(dataframe.head())

print("\nDataset Information:") print(dataframe.info()) if 'rate' in dataframe.columns: def handle_rate(value): try: value = str(value).split('/')[0] # Extract numeric part before '/' return float(value) if value.replace('.', '', 1).isdigit() else None except (ValueError, AttributeError, TypeError): return None

dataframe['rate'] = dataframe['rate'].apply(handle_rate)

print("\nData after processing 'rate' column:")
print(dataframe[['rate']].head())  # Show only the 'rate' column for clarity

else: print("\nColumn 'rate' not found in the dataset. Check CSV file.") print("\nUpdated DataFrame Info:") print(dataframe.info())

print("\nFirst few rows of the cleaned dataset:") print(dataframe.head()) dataframe.to_csv("Cleaned_Zomato_data.csv", index=False) sns.countplot(x=dataframe['listed_in(type)']) plt.xlabel("type of resturant") dataframe.head() grouped_data = dataframe.groupby('listed_in(type)')['votes'].sum() result = pd.DataFrame({'votes': grouped_data}) plt.figure(figsize=(10, 5)) # Set figure size plt.plot(result.index, result['votes'], color="green", marker="o", linestyle="-")
plt.xlabel("Types of Restaurant", color="red", fontsize=15) plt.ylabel("Votes", color="red", fontsize=15) plt.title("Total Votes by Restaurant Type", fontsize=18) plt.xticks(rotation=45) plt.show() dataframe.head() plt.hist(dataframe['rate'],bins=5) plt.title("rating distribution") plt.show() dataframe.head() couple_data=dataframe['approx_cost(for two people)'] sns.countplot(x=couple_data) dataframe.head() plt.figure(figsize=(6,6)) # Set figure size

Create a boxplot

sns.boxplot(x='online_order', y='rate', data=dataframe)

Labeling

plt.xlabel("Online Order Availability", color="blue", fontsize=14) plt.ylabel("Restaurant Rating", color="blue", fontsize=14) plt.title("Boxplot of Ratings by Online Order Availability", fontsize=16)

Show the plot

plt.show()

Ensure column names are correct

if 'listed_in(type)' in dataframe.columns and 'online_order' in dataframe.columns:

Create a pivot table

pivot_table = dataframe.pivot_table(
    index='listed_in(type)', 
    columns='online_order', 
    aggfunc='size', 
    fill_value=0
)

Plot heatmap

plt.figure(figsize=(8,6))
sns.heatmap(pivot_table, annot=True, cmap='YlGnBu', fmt='d')

# Labels and title
plt.title("Heatmap of Online Orders by Restaurant Type", fontsize=14)
plt.xlabel("Online Order Availability", fontsize=12, color="blue")
plt.ylabel("Restaurant Type", fontsize=12, color="blue")

# Show plot
plt.show()

else: print("One or both of the required columns ('listed_in(type)', 'online_order') are missing.")