How can i merge two columns into one (final output) (python/sqlite)

Question

How can i merge two columns into one (final output) (python/sqlite)

import sqlite3
import pandas as pd

# load data
df = pd.read_csv('CurriculumAuditReport.csv')

# strip whitespace from headers
df.columns = df.columns.str.strip()

con = sqlite3.connect("sans.db")

# drop data into database
df.to_sql("MyTable", con, if_exists='replace')

qry = """
SELECT department, count(*) as cnt
FROM MyTable
WHERE CompletedTraining = 'Incomplete'
GROUP BY department
"""

qry2 = """
SELECT [Employee Name], Department, [Date Assigned] FROM MyTable Where CompletedTraining ='Incomplete' ORDER BY Department ASC
"""


df = pd.read_sql_query(qry, con)
df2 = pd.read_sql_query(qry2, con)

print(df.to_json())
print(df2)


con.close()

can i merge department with cnt? so that i have AQPSD: 6, ASD: 8, CO: 2 ect???

currently: 2 columns as expected

   Department  count(*)

0       AQPSD         6
1         ASD         8
2          CO         2
3       ECARS         3
4          ED         6
5          EO         4
6         ISD         4
7        MSCD         5
8         OIS         1
9          RD         2
10        TTD         4

this has the following Output: 1 column (kind of hard to display but its my end goal)

Department

0       AQPSD 6
1         ASD 8
2          CO 2
3       ECARS 3
4          ED 6
5          EO 4
6         ISD 4
7        MSCD 5
8         OIS 1
9          RD 2
10        TTD 4

Answer 1

You can either do it on the SQLite side or in Pandas.

Option 1 (using SQLite):

qry = """
SELECT department || ' ' || cast(count(*) as text) as col_name
FROM MyTable
WHERE CompletedTraining = 'Incomplete'
GROUP BY department
"""
df = pd.read_sql(qry, con)

Option 2 (using Pandas):

assuming we have the following DataFrame:

In [79]: df
Out[79]:
   department  cnt
0       AQPSD    6
1         ASD    8
2          CO    2
3       ECARS    3
4          ED    6
5          EO    4
6         ISD    4
7        MSCD    5
8         OIS    1
9          RD    2
10        TTD    4

let's convert it to a single column DF:

In [80]: df['department'] = df['department'] + ' ' + df.pop('cnt').astype(str)

In [81]: df
Out[81]:
   department
0     AQPSD 6
1       ASD 8
2        CO 2
3     ECARS 3
4        ED 6
5        EO 4
6       ISD 4
7      MSCD 5
8       OIS 1
9        RD 2
10      TTD 4

PS this can easily be done without using SQLite at all, but we would need a small reproducible sample data set in the original format (which would reproduce data from CurriculumAuditReport.csv )

Answer 2

This is a step by step solution:

Add a new column and convert the count column to string with "astype(str)

df['new_column'] = df['Department'] + " " + df['count'].astype(str)

Delete columns that you don't need

del df['Department']
del df['count']

Rename new_column

df.rename(columns={'new_column': 'Department'}, inplace=True)

I know it has a lot of steps, but sometimes is better to break it down in small steps to have a better understanding.