Week 1: Assignment ~ Selecting a Data Set¶
About my dataset
This dataset presents total morbidity at the national level, categorized by disease type, age group, and gender. It uses ICD-10 codes to classify diseases across a wide range of health conditions, including infectious diseases, viral and parasitic diseases, neoplasms, blood disorders, endocrine and metabolic disorders, mental health conditions, nervous system disorders, eye and ear diseases, circulatory and respiratory system diseases, digestive system conditions, skin and musculoskeletal disorders, genitourinary conditions, pregnancy-related complications, congenital abnormalities, injuries, and other health-related conditions.
For each condition, the dataset provides the number of cases for males and females in different age groups, ranging from 0-29 days to 60+ years. This detailed data allows for analysis of disease distribution, priority health problems, age and gender trends, and national morbidity patterns, which can be useful for public health planning, epidemiological studies, and resource allocation.
Reference
Royal Government of Bhutan, Ministry of Health. (2024). Annual health statistics 2023. Open Government Data Portal, Bhutan. https://data.gov.bt/ministry-of-health/annual-health-statistics
import pandas as pd
df = pd.read_csv('datasets/DataSet_CommonDiseases.csv')
print(df) # Full dataset (may be truncated)
Name of the Diseases 0-29 Days Unnamed: 2 1-11 Months \
0 NaN M F M
1 NaN NaN NaN NaN
2 Diarrhoea 68 66 928
3 Dysentery 6 1 59
4 TuberculosisB 1 NaN 3
.. ... ... ... ...
137 PRIORITY HEALTH PROBLEM/DISEASE 0-29 Days NaN 1-11 Months
138 NaN NaN NaN NaN
139 Complications of Health Care 13 15 14
140 ANC, Immunization & Other Counselling 588 576 3428
141 TOTAL OLD CASES ALL CAUSES 877541 NaN NaN
Unnamed: 4 1-4 Years Unnamed: 6 5-9 Years Unnamed: 8 10-14 Years ... \
0 F M F M F M ...
1 NaN NaN NaN NaN NaN NaN ...
2 906 3303 2800 2007 1753 1717 ...
3 41 151 138 122 122 131 ...
4 NaN 1 1 1 2 3 ...
.. ... ... ... ... ... ... ...
137 NaN 1-4 Years NaN 5-9 Years NaN 10-14 Years ...
138 NaN NaN NaN NaN NaN NaN ...
139 20 35 39 20 12 21 ...
140 3388 4584 4587 1393 1412 1140 ...
141 NaN NaN NaN NaN NaN NaN ...
15-19 Years Unnamed: 12 20-24 Years Unnamed: 14 25-49 Years \
0 M F M F M
1 NaN NaN NaN NaN NaN
2 1230 997 991 920 2722
3 143 147 178 153 366
4 29 44 57 68 153
.. ... ... ... ... ...
137 15-19 Years NaN 20-24 Years NaN 25-49 Years
138 NaN NaN NaN NaN NaN
139 21 13 22 33 138
140 940 1403 1100 4470 6687
141 NaN NaN NaN NaN NaN
Unnamed: 16 50-59 Years Unnamed: 18 60+ Years Unnamed: 20
0 F M F M F
1 NaN NaN NaN NaN NaN
2 2928 801 865 1318 1387
3 408 179 167 179 187
4 129 37 31 76 52
.. ... ... ... ... ...
137 NaN 50-59 Years NaN 60+ Years NaN
138 NaN NaN NaN NaN NaN
139 198 46 33 68 37
140 24391 1918 3116 2956 3295
141 NaN NaN NaN NaN NaN
[142 rows x 21 columns]