-
Notifications
You must be signed in to change notification settings - Fork 0
/
columb.py
24 lines (21 loc) · 1.14 KB
/
columb.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
import pandas as pd
from io import StringIO
import matplotlib.pyplot as plt
# Paste your dataset here or specify a file path
data = """
age,workclass,fnlwgt,education,education-num,marital-status,occupation,relationship,race,sex,capital-gain,capital-loss,hours-per-week,native-country,class
39,State-gov,77516,Bachelors,13,Married-civ-spouse,Adm-clerical,Wife,White,Female,2174,0,40,United-States,<=50K
50,Self-emp-not-inc,83311,Bachelors,13,Divorced,Exec-managerial,Not-in-family,White,Male,0,0,13,United-States,<=50K
38,Private,215646,HS-grad,9,Married-civ-spouse,Handlers-cleaners,Wife,White,Female,0,0,40,United-States,<=50K
53,Private,234721,11th,7,Divorced,Handlers-cleaners,Not-in-family,Black,Female,0,0,40,United-States,<=50K
28,Private,338409,Bachelors,13,Divorced,Prof-specialty,Unmarried,Asian-Pac-Islander,Male,0,0,40,Cambodia,<=50K
"""
# Reading data as a file using StringIO
df = pd.read_csv(StringIO(data))
# Drawing column chart based on "race" property
race_counts = df['race'].value_counts()
race_counts.plot(kind='bar', color='skyblue', edgecolor='black')
plt.title('Distribution of ras')
plt.xlabel('Race')
plt.ylabel('Frequency')
plt.show()