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Using Python, perform data analysis on the attached csv file regarding alzheimers. Then Study and analyze the dataset to find correlations between the average age of patients, average race of...

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Using Python, perform data analysis on the attached csv file regarding alzheimers. Then Study and analyze the dataset to find correlations between the average age of patients, average race of patients, and comparison of patient’s age and race with Alzheimer’s as well as any other data analysis. Create visualizations of each analysis through numpy or other means. Create advanced analysis and add more information to the PowerPoint that explains the visualizations more in detail and helps the reader truly understand the information/possibly pull more information.
Answered 5 days AfterMar 14, 2022

Solution

Pawan answered on Mar 19 2022
69 Votes
19/03/2022, 14:19 analysis - Jupyter Notebook
localhost:8888/notebooks/analysis.ipynb# 1/8
In [108]:
In [121]:
After observing the database, the following the values are present
Out[121]:
CONDITION OUTCOME Year Geography GeoType GeoName GeoID
0 Alzheimer'sDisease Death 2017 El Cajon SRA EL CAJON 34
1 Alzheimer'sDisease Death 2017 Ha
ison Crest SRA HARBISON CREST 37
2 Alzheimer'sDisease Death 2017
Ha
ison
Crest-El Cajon NaN
HARBISON CREST-
EL CAJON 99
3 Alzheimer'sDisease Death 2017 Jamul SRA JAMUL 30
4 Alzheimer'sDisease Death 2017 La Mesa SRA LA MESA 33
... ... ... ... ... ... ... ...
3061 Alzheimer'sDisease
SNF/Intermediate
Care 2011
City of San
Marcos Municipal SAN MARCOS 15
3062 Alzheimer'sDisease
SNF/Intermediate
Care 2011 City of Santee Municipal SANTEE 16
3063 Alzheimer'sDisease
SNF/Intermediate
Care 2011
City of Solana
Beach Municipal SOLANA BEACH 17
3064 Alzheimer'sDisease
SNF/Intermediate
Care 2011 City of Vista Municipal VISTA 18
3065 Alzheimer'sDisease
SNF/Intermediate
Care 2011 Unincorporated Municipal UNINCORPORATED 19
3066 rows × 278 columns
import numpy as np
import pandas as pd
%matplotlib notebook
import matplotlib.pyplot as plt
data = pd.read_csv("alzheimersdisease.csv", delimiter=",", low_memory=False)
data
19/03/2022, 14:19 analysis - Jupyter Notebook
localhost:8888/notebooks/analysis.ipynb# 2/8
In [122]:
In [156]:
aces = ['White', 'Black', 'Hispanic', 'API', 'AIAN', 'Other_notAIAN']
AgeGroups =["0_14", "15_24", "25_44", "45_64", "65Plus"]
Gender = ["Male", "Female"]
def...
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