It is an old dataset and the only shortcoming is that it is less likely to tell us the 2020 or 2021 reality The story here is about how Non-hispanic white have in recent years are increasingly being more impacted by the diseases of heart, while the death rate of the same among the black community has reduced. It would be interesting to find out the reason behind this flip. Like what is being done in the black community to bring down the rate And why the death rate is increasing in non-hispanic white.

import pandas as pd

import altair as alt

df = pd.read_csv('New_York_City_Leading_Causes_of_Death.csv')
df.head(2)

	Year	Leading Cause	Sex	Race Ethnicity	Deaths	Death Rate	Age Adjusted Death Rate
0	2015	Malignant Neoplasms (Cancer: C00-C97)	Female	Asian and Pacific Islander	515	79.72666911	78.86538643
1	2015	Diseases of Heart (I00-I09, I11, I13, I20-I51)	Female	Asian and Pacific Islander	498	77.09491499	81.60513144


df.shape

(1516, 7)

alt.Chart(df.head(10)).mark_bar().encode(
    x = 'Death Rate:Q',
    y = 'Leading Cause:N',
    tooltip = 'Race Ethnicity',
)

#this is what I was hoping for, but it is tiny
alt.Chart(df.head(10)).mark_point( filled=True,
    size=100).encode(
    x = 'Death Rate:Q',
    y = 'Race Ethnicity:N',
    tooltip = 'Leading Cause',
)

df.head(2)

	Year	Leading Cause	Sex	Race Ethnicity	Deaths	Death Rate	Age Adjusted Death Rate
0	2015	Malignant Neoplasms (Cancer: C00-C97)	Female	Asian and Pacific Islander	515	79.72666911	78.86538643
1	2015	Diseases of Heart (I00-I09, I11, I13, I20-I51)	Female	Asian and Pacific Islander	498	77.09491499	81.60513144


alt.Chart(df).mark_point().encode(
    x = 'Year:N',
    y = 'Death Rate:Q',
    tooltip = 'Leading Cause',
     color = 'Race Ethnicity'
)

NON-COMMUNICABLE DISEASES IN NYC AND ITS EFFECTS ON ETHNIC GROUPS