def all_plots_dashboard_dict(query_components): conn = get_db_connection() cursor = conn.cursor(as_dict=True) age_group = age_group_plot_data(cursor, query_components) gauge = random.randint(80, 90) conn.close() python_dict = {"age_group": age_group, "gauge": gauge} return python_dict
def get_date_recent(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT RecencyTest_Date,COUNT(New_HIV_Diagnosis_and_Recency_Test_taken) AS Count FROM HIV_Sample_tables WHERE New_HIV_Diagnosis_and_Recency_Test_taken = 'Recent' GROUP BY RecencyTest_Date; ''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def get_age_count_recent(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT Age_Group,COUNT(*) AS Count FROM HIV_Sample_tables GROUP BY Age_Group,New_HIV_Diagnosis_and_Recency_Test_taken HAVING New_HIV_Diagnosis_and_Recency_Test_taken = 'Recent' ORDER BY Age_Group;''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def get_site_count_LT(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT Site_ID,COUNT(*) AS Count FROM HIV_Sample_tables GROUP BY Site_ID,New_HIV_Diagnosis_and_Recency_Test_taken HAVING New_HIV_Diagnosis_and_Recency_Test_taken = 'Long-term' ORDER BY Site_ID;''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def get_contact_test_count(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT Index_Test,COUNT(*) AS Count FROM HIV_Sample_tables GROUP BY Index_Test ORDER BY Index_Test; ''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def new_hiv_count(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT New_HIV_Diagnosis_and_Recency_Test_taken,COUNT(*) AS Count FROM HIV_Sample_tables GROUP BY New_HIV_Diagnosis_and_Recency_Test_taken ORDER BY New_HIV_Diagnosis_and_Recency_Test_taken;;;; ''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def get_risk_count(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT Transmission_Category,COUNT(*) AS Count FROM HIV_Sample_tables GROUP BY Transmission_Category ORDER BY Transmission_Category;; ''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d
def get_trgender(): # Extract Data from Microsoft SQL Server conn = get_db_connection() SQL_Query = pd.read_sql_query( '''SELECT DATEPART(month, RecencyTest_Date) AS Month,COUNT(New_HIV_Diagnosis_and_Recency_Test_taken) AS Count FROM HIV_Sample_tables WHERE Sex = 'Trangender' GROUP BY DATEPART(month, RecencyTest_Date) order by Month;; ''', conn) d = pd.DataFrame(SQL_Query) conn.close() return d