Purpose

Remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe.

To Elaborate

The Python script aims to remove the dollar sign ($) from the SBA Campaign Budget column in a given input dataframe. The SBA Campaign Budget column contains budget values for different campaigns, but some of the values have a dollar sign ($) at the beginning. This script removes the dollar sign ($) from those values, ensuring that the budget values are in a consistent format for further analysis or processing.

Walking Through the Code

1. The input dataframe is retrieved from the dataSourceDict dictionary using the key “1”.
2. The script defines the names of the output columns and their initial values.
3. The dollar sign ($) is removed from the beginning of values in the RPT_COL_SBA_CAMPAIGN_BUDGET column in the input dataframe.
4. Only non-empty rows in the BULK_COL_SBA_CAMPAIGN_BUDGET column of the output dataframe are included.
5. The dollar sign ($) is removed from the beginning of values in the BULK_COL_SBA_CAMPAIGN_BUDGET column in the output dataframe.
6. If the output dataframe is not empty, it is printed in a tabular format using the tableize() function. Otherwise, the message “Empty outputDf” is printed.

Vitals

• Script ID : 789
• Client ID / Customer ID: 1306926629 / 60270083
• Action Type: Bulk Upload
• Item Changed: Campaign
• Output Columns: Account, Campaign, SBA Campaign Budget
• Linked Datasource: M1 Report
• Reference Datasource: None
• Owner: dwaidhas@marinsoftware.com (dwaidhas@marinsoftware.com)
• Created by dwaidhas@marinsoftware.com on 2024-03-08 22:11
• Last Updated by dwaidhas@marinsoftware.com on 2024-03-08 22:14

> See it in Action

Python Code

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
##
## name: Remove $ from SBA Campaign Budget
## description:
##  
## 
## author: 
## created: 2024-03-08
## 

inputDf = dataSourceDict["1"]

# Output columns and initial values
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_SBA_CAMPAIGN_BUDGET = 'SBA Campaign Budget'
RPT_COL_CAMPAIGN_STATUS = 'Campaign Status'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_SBA_CAMPAIGN_BUDGET = 'SBA Campaign Budget'

# Remove '$' from the beginning of values in the RPT_COL_SBA_CAMPAIGN_BUDGET column in inputDf
inputDf[RPT_COL_SBA_CAMPAIGN_BUDGET] = inputDf[RPT_COL_SBA_CAMPAIGN_BUDGET].str.replace('$', '')

# Only include non-empty tags in bulk
outputDf = outputDf.dropna(subset=[BULK_COL_SBA_CAMPAIGN_BUDGET])

# Remove '$' from the beginning of values in the BULK_COL_SBA_CAMPAIGN_BUDGET column in outputDf
outputDf[BULK_COL_SBA_CAMPAIGN_BUDGET] = outputDf[BULK_COL_SBA_CAMPAIGN_BUDGET].str.replace('$', '')

if not outputDf.empty:
    print("outputDf", tableize(outputDf))
else:
    print("Empty outputDf")

Post generated on 2024-03-10 06:34:12 GMT