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# This Python 3 environment comes with many helpful analytics libraries installed
# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python
# For example, here's several helpful packages to load

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

# Input data files are available in the read-only "../input/" directory
# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory

import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))

# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using "Save & Run All" 
# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session
df = pd.read_csv('data.csv')
df.head(20)
df.info()
<class 'pandas.core.frame.DataFrame'> RangeIndex: 569 entries, 0 to 568 Data columns (total 33 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 id 569 non-null int64 1 diagnosis 569 non-null object 2 radius_mean 569 non-null float64 3 texture_mean 569 non-null float64 4 perimeter_mean 569 non-null float64 5 area_mean 569 non-null float64 6 smoothness_mean 569 non-null float64 7 compactness_mean 569 non-null float64 8 concavity_mean 569 non-null float64 9 concave points_mean 569 non-null float64 10 symmetry_mean 569 non-null float64 11 fractal_dimension_mean 569 non-null float64 12 radius_se 569 non-null float64 13 texture_se 569 non-null float64 14 perimeter_se 569 non-null float64 15 area_se 569 non-null float64 16 smoothness_se 569 non-null float64 17 compactness_se 569 non-null float64 18 concavity_se 569 non-null float64 19 concave points_se 569 non-null float64 20 symmetry_se 569 non-null float64 21 fractal_dimension_se 569 non-null float64 22 radius_worst 569 non-null float64 23 texture_worst 569 non-null float64 24 perimeter_worst 569 non-null float64 25 area_worst 569 non-null float64 26 smoothness_worst 569 non-null float64 27 compactness_worst 569 non-null float64 28 concavity_worst 569 non-null float64 29 concave points_worst 569 non-null float64 30 symmetry_worst 569 non-null float64 31 fractal_dimension_worst 569 non-null float64 32 Unnamed: 32 0 non-null float64 dtypes: float64(31), int64(1), object(1) memory usage: 146.8+ KB 
df.diagnosis.value_counts()
B    357
M    212
Name: diagnosis, dtype: int64
import matplotlib.pyplot as plt
import seaborn as sns