Visualizations were created using R. Open source code is available on GitHub.
The ledger took note of what was thought to be the cause of each patient’s illness. Supposed causes have been cleaned in preparation for analysis. Supposed causes have been categorized as either situational or physical. Additionally, supposed causes have been categorized.
The table below shows the supposed causes as transcribed from the ledger and their frequencies.
To compare, the visualizations below show the cleaned and categorized supposed causes and their frequencies in the ledger.
Frequencies of Supposed Causes67.5% of admissions (5050) had supposed causes recorded. 2429 admissions with unknown or unrecorded supposed causes have been excluded from this visualization.
The interactive sunburst charts below show supposed causes by gender. Gender was missing for 1.6% (123) of admissions and have been excluded from these visualizations. A total of 3525 women and 3831 men were admitted between 1856-1916.
Supposed causes by Gender: Male68.3% of admissions of men (2617) had supposed causes recorded. 1214 admissions of men with unknown or unrecorded supposed causes have been excluded from this visualization.
Supposed causes by Gender: Female67.2% of admissions of women (2372) had supposed causes recorded. 1153 women with unknown or unrecorded supposed causes have been excluded from this visualization.
Diagnoses, or forms of illness, were noted in the ledger for 92.8% (6937) of admissions. 542 admissions with unknown or unrecorded supposed causes have been excluded from the following visualization.
Patients had their occupations recorded at each admission. Occupations have been cleaned into categories to facilitate visualization. 1582 admissions had unknown occupations and have been excluded from this visualization.
Patients’ county of residence was recorded at each admission. 0.2% of admissions (14) did not have county of residence recorded, and 0.4% of admissions (27) resided out of state. Other states of residence included Alabama, Arkansas, California, Florida, Georgia, Mississippi, New York, Ohio, South Carolina, Tennessee, and Virginia. These admissions are not represented in the maps below.
County census data and shapefiles are from IPUMS NHGIS, University of Minnesota.