AIM-PIbd-32-Borovkov-M-V/Lab_1/lab1.ipynb

In [78]:

import pandas as pd

df = pd.read_csv("../data/healthcare-dataset-stroke-data.csv", index_col="id")

data = df.copy()
hypertension_df = data[data["hypertension"] == 1]
heart_disease_df = data[data["heart_disease"] == 1]

hypertension_df.groupby(["gender"]).size().plot(kind='pie', y='gender', autopct='%1.0f%%')

Out[78]:

<Axes: >

In [79]:

heart_disease_df.groupby(["gender"]).size().plot(kind='pie', y='gender', autopct='%1.0f%%')

Out[79]:

<Axes: >

In [80]:

hypertension_df.plot.hist(column=["age"], bins=80)

Out[80]:

<Axes: ylabel='Frequency'>

In [81]:

heart_disease_df.plot.hist(column=["age"], bins=80)

Out[81]:

<Axes: ylabel='Frequency'>

In [82]:

heart_disease_df.groupby(["work_type"]).size().plot(kind='pie', y='work_type', autopct='%1.2f%%')

Out[82]:

<Axes: >

In [83]:

hypertension_df.groupby(["work_type"]).size().plot(kind='pie', y='work_type', autopct='%1.2f%%')

Out[83]:

<Axes: >

In [84]:

df = data[['age', 'hypertension', 'heart_disease']].groupby(['age']).agg(
    hypertension=pd.NamedAgg(column="hypertension", aggfunc="sum"),
    heart_disease=pd.NamedAgg(column="heart_disease", aggfunc="sum")
)
plt.plot(df)

Out[84]:

[<matplotlib.lines.Line2D at 0x18576a5a450>,
 <matplotlib.lines.Line2D at 0x18576be13a0>]

In [84]:

In [84]: