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Finalized SKUID script! Attempts at json to csv script.

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This commit is contained in:
Norm Rasmussen
2022-12-09 23:25:44 -05:00
parent 5742d0401c
commit c8fa672a7b
31 changed files with 7280 additions and 325 deletions
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42
Scripts/Skuid_LPs/find_completed.py
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@ -35,9 +35,9 @@ def lpLevels(basecsv, lpcsv):
index_col=1,
)
newDf = levels.groupby("Learning Path")
learningpaths = newDf.apply(lambda x: x["Course Name"].unique())
# learningpaths = newDf2.apply(pd.Series)
# learningpaths.rename_axis(index=0)
newDf2 = newDf.apply(lambda x: x["Course Name"].unique())
learningpaths = newDf2.apply(pd.Series)
learningpaths.rename_axis(index=0)
mainFunc(basecsv, learningpaths)
# print(levels.Level.unique()) # Print only unique values from the Level column
@ -54,42 +54,22 @@ def mainFunc(basecsv, learningpaths):
# This prints a dataframe with the learner's name as the index column and the courses as adjacent columns
# Part 2
# learningpaths.set_index(0)
courses = learningpaths.set_index(0)
# print(courses)
lp_dict = learningpaths.to_dict()
courses = lp_dict.values()
print(courses)
# crs = courses
# print(crs)
# lp_dict = learningpaths.to_dict("index")
# courses = lp_dict.values()
# Part 3
# for course in courses:
# print(df2.isin(course))
print(df2.isin(df2))
# This produces a bunch of T/F in the dataframe. Is the solution to do:
# for courses in lp_dict, for row(person) in readData
# if number of True == length/# of values in courses
# Add to "Finished List"
# df3 = df2.columns
# print(df3)
# for name in df3.items():
# print(f"name: {name}")
# emailGroups = readData.groupby(["Email", "Learner Full Name"])["Course Name"].nunique()
# print(emailGroups)
# emailGroups = people.to_csv(
# "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/outtest2.csv"
# )
# if readData.loc[readData['Course Name'].isin([
# 'Get Started with Models - Level 1',
# 'Configure Model Fields - Level 1',
# 'Configure Model Conditions - Level 1',
# 'Configure Model Actions - Level 1',
# 'Manage Models - Level 1',
# 'Intro to UI Only Fields - Level 1'])]:
# extractedList = readData.loc[readData['Email'].tolist()]
# fourOccs = Counter(extractedList)
# finalNames = []
# for name, occurrences in fourOccs.items():
# if occurrences == 6:
# finalNames.append(name)
if __name__ == "__main__":
# mainFunc(basecsv)