├── README.md
├── python.py
└── shivam12315706 (1).pdf


/README.md:
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1 | # python.project


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/python.py:
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 1 | import pandas as pd
 2 | import seaborn as sns
 3 | import matplotlib.pyplot as plt
 4 | 
 5 | # Load the Excel file into a DataFra
 6 | data_path = r"C:\Users\ASUS\OneDrive\Desktop\DataSet Employment.xlsx"
 7 | df = pd.read_excel(data_path)
 8 | # Set up a plot style
 9 | sns.set(style="whitegrid")
10 | # 1. Histogram  
11 | plt.figure(figsize=(6, 4))
12 | sns.histplot(df["Employment Rate"], kde=True, color="skyblue", bins=10)
13 | plt.title("Histogram of Employment Rate")
14 | plt.xlabel("Employment Rate")
15 | plt.ylabel("Frequency")
16 | plt.show()
17 | # 2. Bar Plot (Average Employment Rate by Region)
18 | plt.figure(figsize=(6, 4))
19 | sns.barplot(x="Region", y="Employment Rate", data=df, palette="Set2")
20 | plt.title("Average Employment Rate by Region")
21 | plt.xlabel("Region")
22 | plt.ylabel("Employment Rate")
23 | plt.xticks(rotation=45)  # In case region labels are long
24 | plt.show()
25 | 
26 | # 3. Scatter Plot (Employment Rate vs GDP)
27 | plt.figure(figsize=(6, 4))
28 | sns.scatterplot(x="GDP", y="Employment Rate", data=df, hue="Region", palette="coolwarm", s=100)
29 | plt.title("Employment Rate vs GDP")
30 | plt.xlabel("GDP")
31 | plt.ylabel("Employment Rate")
32 | plt.show()
33 | 


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/shivam12315706 (1).pdf:
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https://raw.githubusercontent.com/shivamgill9322/python.project/ffdc0b92731c5dd2172555baf9ce7e8a206c884d/shivam12315706 (1).pdf


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