📊 Dataset · CSV

breast_cancer.csv

Name: breast_cancer.csv
Creator: Mathew K
License: https://creativecommons.org/licenses/by/4.0/

Free CSV dataset “breast_cancer.csv” (569 rows × 31 columns, 118.5 KB) used in 3 Python lessons, including “Logistic Regression for Classification | ML…

⬇ Download CSV (118.5 KB)

Size118.5 KB
Rows569
Columns31
Used in3 lessons

Preview (first rows)

mean radius	mean texture	mean perimeter	mean area	mean smoothness	mean compactness	mean concavity	mean concave points	mean symmetry	mean fractal dimension	radius error	texture error
17.99	10.38	122.8	1001.0	0.1184	0.2776	0.3001	0.1471	0.2419	0.07871	1.095	0.9053
20.57	17.77	132.9	1326.0	0.08474	0.07864	0.0869	0.07017	0.1812	0.05667	0.5435	0.7339
19.69	21.25	130.0	1203.0	0.1096	0.1599	0.1974	0.1279	0.2069	0.05999	0.7456	0.7869
11.42	20.38	77.58	386.1	0.1425	0.2839	0.2414	0.1052	0.2597	0.09744	0.4956	1.156
20.29	14.34	135.1	1297.0	0.1003	0.1328	0.198	0.1043	0.1809	0.05883	0.7572	0.7813
12.45	15.7	82.57	477.1	0.1278	0.17	0.1578	0.08089	0.2087	0.07613	0.3345	0.8902
18.25	19.98	119.6	1040.0	0.09463	0.109	0.1127	0.074	0.1794	0.05742	0.4467	0.7732
13.71	20.83	90.2	577.9	0.1189	0.1645	0.09366	0.05985	0.2196	0.07451	0.5835	1.377

+ 19 more columns

Columns

Column	Type	Example
`mean radius`	decimal	17.99
`mean texture`	decimal	10.38
`mean perimeter`	decimal	122.8
`mean area`	decimal	1001.0
`mean smoothness`	decimal	0.1184
`mean compactness`	decimal	0.2776
`mean concavity`	decimal	0.3001
`mean concave points`	decimal	0.1471
`mean symmetry`	decimal	0.2419
`mean fractal dimension`	decimal	0.07871
`radius error`	decimal	1.095
`texture error`	decimal	0.9053
`perimeter error`	decimal	8.589
`area error`	decimal	153.4
`smoothness error`	decimal	0.006399
`compactness error`	decimal	0.04904
`concavity error`	decimal	0.05373
`concave points error`	decimal	0.01587
`symmetry error`	decimal	0.03003
`fractal dimension error`	decimal	0.006193
`worst radius`	decimal	25.38
`worst texture`	decimal	17.33
`worst perimeter`	decimal	184.6
`worst area`	decimal	2019.0
`worst smoothness`	decimal	0.1622
`worst compactness`	decimal	0.6656
`worst concavity`	decimal	0.7119
`worst concave points`	decimal	0.2654
`worst symmetry`	decimal	0.4601
`worst fractal dimension`	decimal	0.1189
`target`	integer	0

Load it in Python

import pandas as pd
df = pd.read_csv("breast_cancer.csv")
df.head()

breast_cancer.csv

Preview (first rows)

Columns

Load it in Python

Lessons that use this dataset

Logistic Regression for Classification | ML Algorithms #2

K-Nearest Neighbours (KNN) Explained | ML Algorithms #3

Support Vector Machines Made Intuitive | ML Algorithms #7