how to divide two columns in sqlalchemy

Last Updated : 28 Feb, 2022,Geeks-Premier-League-2022

pip install sqlalchemy pymysql

SELECT column1 / column2 FROM table_name;

SELECT column1, column2 FROM table_name;

Does anyone know what could be wrong in the query above and how to fix it in order to divide column total_duration from table t1 with column total_events_duration from table t2?,I tried to divide two columns from joined tables but the result (value of column relative_duration) is always 0. The query is the following:,BTW I tried to replace division with subtraction (“/” with “-“) and in that case the column relative_duration is not 0.,you will get 0, which is obviously not the real answer. So, convert the values to e.g. decimal and do the calculation based on that datatype instead.

    SELECT t1.[user_1], t1.[user_2], t1.[total_duration], (t1.total_duration / t2.[total_events_duration]) AS relative_duration
    FROM[CDRs].[dbo].[aggregate_monthly_events] AS t1 INNER JOIN[CDRs].[dbo].[user_events_monthly_stats] AS t2 ON t1.[user_1] = t2.[user_1]

SELECT 1 / 2

SELECT CAST(1 AS DECIMAL) / 2

The second method to divide two columns is using the div() method. It divides the columns elementwise. It accepts a scalar value, series, or dataframe as an argument for dividing with the axis. If the axis is 0 the division is done row-wise and if the axis is 1 then division is done column-wise.,The first method you can use to divide two columns is the simple division (/) operator. Here you will divide column1 with other columns.,It accepts three arguments. One is the condition, second is the results and third is the value where the condition is not met. In our case, I am using the NaN value.,Pandas python module can do fast manipulation on any dataframe. These are the method to divide two columns in dataframe. You can use any of them. I hope you have liked this tutorial. If you have any queries then you can contact us for more help.

import pandas as pd
data = {
   "col1": [100, 200, 300, 400, 500],
   "col2": [10, 20, 30, 40, 50]
}
df = pd.DataFrame(data)
df["result"] = df["col1"] / df["col2"]
print(df)

An alternative to cast() is the type_coerce() function. This function performs the second task of associating an expression with a specific type, but does not render the CAST expression in SQL.,Changed in version 1.4: the case() function now accepts the series of WHEN conditions positionally; passing the expressions within a list is deprecated.,The cast() function performs two distinct functions when used. The first is that it renders the CAST expression within the resulting SQL string. The second is that it associates the given type (e.g. TypeEngine class or instance) with the column expression on the Python side, which means the expression will take on the expression operator behavior associated with that type, as well as the bound-value handling and result-row-handling behavior of the type.,The TextClause construct is produced using the text() function; see that function for full documentation.

from sqlalchemy
import and_

stmt = select(users_table).where(
   and_(
      users_table.c.name == 'wendy',
      users_table.c.enrolled == True
   )
)

stmt = select(users_table).where(
   (users_table.c.name == 'wendy') &
   (users_table.c.enrolled == True)
)

stmt = select(users_table).\
where(users_table.c.name == 'wendy').\
where(users_table.c.enrolled == True)

criteria = and_(True, * expressions)

from sqlalchemy
import bindparam

stmt = select(users_table).\
where(users_table.c.name == bindparam('username'))

SELECT id, name FROM user WHERE name =: username