Best Value Laptop Analysis: Acer Chromebook C910-C2ST

Sep 19, 2024, 11:31 AM

laptop_price_dataset.xlsx

Missing file

Which laptop offers the best value for money?

import pandas as pd

# Load the dataset
df = pd.read_csv('laptop_price_dataset.xlsx')
df.head()
import pandas as pd

# Load the dataset with the correct encoding
df = pd.read_csv('laptop_price_dataset.xlsx', encoding='ascii')
df.head()
It seems there is an issue with reading the file using pd.read_csv because it is an Excel file, not a CSV file. We should use pd.read_excel instead to load the dataset correctly.
import pandas as pd

# Load the dataset using the correct method for Excel files
df = pd.read_excel('laptop_price_dataset.xlsx')
df.head()
To determine which laptop offers the best value for money, we can calculate the price per inch of screen size for each laptop. This will give us an idea of how much screen size we are getting for each euro spent.
Let's proceed with this calculation.
# Calculate the price per inch for each laptop
df['Price_per_Inch'] = df['Price_euros'] / df['Inches']

# Find the laptop with the lowest price per inch
df_best_value = df.loc[df['Price_per_Inch'].idxmin()]
df_best_value
The laptop that offers the best value for money, based on the price per inch of screen size, is the Acer Chromebook C910-C2ST. Here are the details:
  • Company: Acer
  • Product: Chromebook C910-C2ST
  • Type: Notebook
  • Inches: 15.6
  • Screen Resolution: 1366x768
  • CPU: Intel Celeron Dual Core 3205U 1.5GHz
  • RAM: 2GB
  • Memory: 16GB SSD
  • GPU: Intel HD Graphics
  • Operating System: Chrome OS
  • Weight: 2.19kg
  • Price: €199.00
  • Price per Inch: €12.76
This laptop provides the most screen size for each euro spent.
Do you have any other questions or would you like to perform further analysis?

Which laptop is the best deal based on CPU Performance and Ram ?

To determine the best deal based on CPU performance and RAM, we need to consider both the CPU and RAM specifications. Since CPU performance is not directly quantifiable from the given data, we will use a proxy measure by considering the CPU model and clock speed. We will also take into account the amount of RAM.
Let's create a composite score based on CPU clock speed and RAM size to identify the best deal.
import re

# Extract CPU clock speed from the 'Cpu' column
# We assume the clock speed is given in GHz and extract it using a regular expression
def extract_clock_speed(cpu_str):
match = re.search(r'(\d+\.\d+)GHz', cpu_str)
return float(match.group(1)) if match else 0

df['Clock_Speed_GHz'] = df['Cpu'].apply(extract_clock_speed)

# Convert RAM to numeric value (assuming all values are in GB)
def extract_ram(ram_str):
match = re.search(r'(\d+)GB', ram_str)
return int(match.group(1)) if match else 0

df['Ram_GB'] = df['Ram'].apply(extract_ram)

# Create a composite score based on clock speed and RAM
# We will give equal weight to both factors for simplicity
df['Performance_Score'] = df['Clock_Speed_GHz'] + df['Ram_GB']

# Find the laptop with the highest performance score per euro spent
df['Performance_per_Euro'] = df['Performance_Score'] / df['Price_euros']
best_deal_laptop = df.loc[df['Performance_per_Euro'].idxmax()]
best_deal_laptop
The laptop that offers the best deal based on CPU performance and RAM is the Lenovo IdeaPad 110-15IBR. Here are the details:
  • Company: Lenovo
  • Product: IdeaPad 110-15IBR
  • Type: Notebook
  • Inches: 15.6
  • Screen Resolution: 1366x768
  • CPU: Intel Celeron Quad Core N3710 1.6GHz
  • RAM: 8GB
  • Memory: 1TB HDD
  • GPU: Intel HD Graphics 405
  • Operating System: No OS
  • Weight: 2.2kg
  • Price: €329.00
  • Price per Inch: €21.09
  • Clock Speed: 1.6GHz
  • Performance Score: 9.6
  • Performance per Euro: 0.029
This laptop provides the best performance per euro spent based on CPU clock speed and RAM.
Do you have any other questions or would you like to perform further analysis?

Is performance per Euro a good measurement?

Performance per Euro can be a useful measurement, but it has its limitations. Here are some points to consider:

Pros:

  1. Cost Efficiency: It helps identify laptops that provide the most performance for the least amount of money, which is useful for budget-conscious buyers.
  2. Simplified Comparison: It provides a single metric to compare different laptops, making it easier to identify good deals.

Cons:

  1. Oversimplification: It may oversimplify the comparison by not considering other important factors such as build quality, battery life, brand reputation, and additional features.
  2. Subjectivity in Performance: The measurement of performance can be subjective. For example, the clock speed of a CPU and the amount of RAM are not the only indicators of a laptop's performance. Other factors like CPU architecture, GPU performance, and storage type (SSD vs. HDD) also play a significant role.
  3. Ignoring User Needs: Different users have different needs. A laptop that is the best deal in terms of performance per euro may not be the best choice for someone who needs a high-resolution display, lightweight design, or specific software compatibility.

Conclusion:

While performance per euro is a useful metric, it should be used in conjunction with other factors to make a well-rounded decision. It's important to consider the overall value and how well a laptop meets your specific needs.
Would you like to explore other metrics or perform a different analysis?

What are the top 5 laptops based on overall performance?

# Sort the laptops based on the overall performance score
# and select the top 5 laptops
top_5_laptops = df.sort_values(by='Performance_Score', ascending=False).head(5)
top_5_laptops
The top 5 laptops based on overall performance are as follows:
  1. Asus ROG G701VO
    • Type: Gaming
    • Inches: 17.3
    • Screen Resolution: IPS Panel Full HD 1920x1080
    • CPU: Intel Core i7 6820HK 2.7GHz
    • RAM: 64GB
    • Memory: 1TB SSD
    • GPU: Nvidia GeForce GTX 980
    • Operating System: Windows 10
    • Weight: 3.58kg
    • Price: €3975.00
    • Performance Score: 66.7
  2. Lenovo Thinkpad P51
    • Type: Notebook
    • Inches: 15.6
    • Screen Resolution: IPS Panel 4K Ultra HD 3840x2160
    • CPU: Intel Xeon E3-1535M v6 3.1GHz
    • RAM: 32GB
    • Memory: 1TB SSD
    • GPU: Nvidia Quadro M2200M
    • Operating System: Windows 10
    • Weight: 2.5kg
    • Price: €4899.00
    • Performance Score: 35.1
  3. Razer Blade Pro
    • Type: Gaming
    • Inches: 17.3
    • Screen Resolution: 4K Ultra HD / Touchscreen 3840x2160
    • CPU: Intel Core i7 7820HK 2.9GHz
    • RAM: 32GB
    • Memory: 1TB SSD
    • GPU: Nvidia GeForce GTX 1080
    • Operating System: Windows 10
    • Weight: 3.49kg
    • Price: €6099.00
    • Performance Score: 34.9
  4. Asus ROG G703VI-E5062T
    • Type: Gaming
    • Inches: 17.3
    • Screen Resolution: Full HD 1920x1080
    • CPU: Intel Core i7 7820HK 2.9GHz
    • RAM: 32GB
    • Memory: 512GB SSD + 1TB HDD
    • GPU: Nvidia GeForce GTX 1080
    • Operating System: Windows 10
    • Weight: 4.7kg
    • Price: €3890.00
    • Performance Score: 34.9
  5. MSI GT80S 6QF-074US
    • Type: Gaming
    • Inches: 18.4
    • Screen Resolution: Full HD 1920x1080
    • CPU: Intel Core i7 6920HQ 2.9GHz
    • RAM: 32GB
    • Memory: 512GB SSD + 1TB HDD
    • GPU: Nvidia GTX 980 SLI
    • Operating System: Windows 10
    • Weight: 4.4kg
    • Price: €2799.00
    • Performance Score: 34.9
These laptops have the highest performance scores based on their CPU clock speed and RAM.
Do you have any other questions or would you like to perform further analysis?

Can you show a comparison plot of the top 5 laptops based on performance?

import plotly.express as px

# Select relevant columns for the top 5 laptops
comparison_data = top_5_laptops[['Company', 'Product', 'Performance_Score', 'Price_euros']]

# Create a bar plot for comparison
fig = px.bar(comparison_data, x='Product', y='Performance_Score', color='Company',
title='Top 5 Laptops Based on Performance',
labels={'Performance_Score': 'Performance Score', 'Product': 'Laptop Model'},
hover_data=['Price_euros'])

# Show the plot
fig.show()
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