Columns: [Id], [Date, Time]. One-to-one relationship to Table 5.
A:
This is the answer that I got after trying to figure out myself the solution:
df = pd.read_sql_query("SELECT user_id, date, time FROM Table5 WHERE user_id = '1'", conn)
for n in df.select_dtypes(exclude=['object']).select_dtypes(include=['float']).select_dtypes(include=['category']):
#print(n)
#print(df.loc[df['id'] == n['user_id']])
#print(df.loc[df['id'] == n['user_id'], 'date'])
print(df.loc[df['id'] == n['user_id'], 'date'])
Although it did not give me the desired results, the above loop almost did. In order to get the desired result I used this:
#print(n.date)
#print(df[df['id'] == n['user_id']]['date'])
#print(df[df['id'] == n['user_id']]['date'].dt.date)
Lymphocyte proliferative responses of human lymphocytes to tetanus toxin and tetanus toxoid in vitro.
Normal human lymphocytes were examined in vitro to tetanus toxin and tetanus toxoid. Both antigens evoked cell-mediated immune responses as evidenced by responses to purified antigen in vitro. The responses to tetanus toxin were generally higher than those to tetanus
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