30 lines
1.1 KiB
Python
30 lines
1.1 KiB
Python
|
# Filters Brightspace's DataHub's UserEnrollments.csv file for a single college
|
||
|
|
# Install Python on Windows from Powershell by running `python` with no arguments
|
||
|
|
# pip install pandas
|
||
|
|
|
||
|
|
import pandas as pd
|
||
|
|
|
||
|
|
# Variables
|
||
|
|
college = 'KV'
|
||
|
|
ue_input_file = '.\\data\\UserEnrollments.csv'
|
||
|
|
ue_output_file = '.\\data\\UEFiltered' + college + '.csv'
|
||
|
|
ue_field_name = 'RoleName'
|
||
|
|
ue_filter_value = college + ' Instructor'
|
||
|
|
|
||
|
|
users_input_file = '.\\data\\Users.csv'
|
||
|
|
users_output_file = '.\\data\\UsersFiltered' + college + '.csv'
|
||
|
|
users_field_name = 'UserName'
|
||
|
|
users_filter_value = "KV_"
|
||
|
|
|
||
|
|
def filter_csv(input_file, output_file, field_name, filter_value):
|
||
|
|
# Read the CSV file
|
||
|
|
df = pd.read_csv(input_file)
|
||
|
|
|
||
|
|
# Filter the DataFrame based on the field value
|
||
|
|
filtered_df = df[df[field_name].str.contains(filter_value, na=False)]
|
||
|
|
|
||
|
|
# Export the filtered DataFrame to a new CSV file
|
||
|
|
filtered_df.to_csv(output_file, index=False)
|
||
|
|
|
||
|
|
filter_csv(ue_input_file, ue_output_file, ue_field_name, ue_filter_value)
|
||
|
|
filter_csv(users_input_file, users_output_file, users_field_name, users_filter_value)
|