66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
from collections import Counter
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import pandas as pd
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basecsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/skuid_05lp.csv"
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lpcsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/skuidlps.csv"
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'''
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Example multivalue dictionary
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dict = {key1: [value1, value2, value3, value4],
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key2: [value5, value6, value 7],
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}
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So this could be used for each learning path. In other words:
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learning_paths = {'01:Skuid Ethos' : ["Congratulations", "Create", "Skuid Resources"]} etc etc
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Ideally, we will add Alexa's "levels" in this dictionary as well. Could we do:
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learning_paths = {'Level_1': [{'01:Skuid Ethos' : ["Congratulations", "Create", "Skuid Resources"]},
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{'02:Composer' : ["Overview", "Get Started with Composer", "Manage Pages"}]
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{'03:Design System Studio' : ["Get Started with Design Systems", etc etc]},
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'Level_2': [{'10 - Data' : ["Tips to Optimize", "Smarter Conditions"]},
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{'11-Components': ["Battle", "Engage"]},
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]
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}
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How to create this by automation?
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'''
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def lpLevels(lpcsv):
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levels = pd.read_csv(
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lpcsv,
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index_col=False,
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)
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print(levels.Level.unique()) # Print only unique values from the Level column
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def mainFunc(basecsv):
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readData = pd.read_csv(
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basecsv,
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index_col=False,
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)
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readData.drop_duplicates(subset='Course Name', keep="first")
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emailGroups = readData.groupby("Email")["Course Name"].nunique()
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print(emailGroups)
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emailGroups = emailGroups.to_csv('/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/outtest.csv')
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#if readData.loc[readData['Course Name'].isin([
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# 'Get Started with Models - Level 1',
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# 'Configure Model Fields - Level 1',
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# 'Configure Model Conditions - Level 1',
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# 'Configure Model Actions - Level 1',
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# 'Manage Models - Level 1',
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# 'Intro to UI Only Fields - Level 1'])]:
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# extractedList = readData.loc[readData['Email'].tolist()]
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# fourOccs = Counter(extractedList)
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# finalNames = []
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# for name, occurences in fourOccs.items():
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# if occurences == 6:
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# finalNames.append(name)
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if __name__ == "__main__":
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#mainFunc(basecsv)
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lpLevels(lpcsv)
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