Started the reorganization of Scripts for github. Some notes changes.

2023-05-04 16:07:06 -04:00
parent 6a674ca24b
commit 18a266746b
209 changed files with 121 additions and 12181 deletions
--- a/Scripts/API_Tests/manual_lps.py
+++ b/Scripts/API_Tests/manual_lps.py
@ -0,0 +1,59 @@
+from collections import Counter
+import pandas as pd
+import glob
+import re
+
+basecsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/Skuid_MCA125.csv"
+directory = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/LPCSVs/*.csv"
+lpcsv = "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/skuidlps.csv"
+
+# Unfortunately, what this needs is a CSV per learning path/MCA export. That will be painful to run.
+
+
+def manualFunc(lpcsv, directory):
+    lps = pd.read_csv(lpcsv)
+    lpcourses = lps.groupby(["Learning Path"])["Course Name"]
+    coursenums = lpcourses.nunique()
+    coursenums = coursenums.to_dict()
+    lpnames = coursenums.keys()
+    # print(lpnames)
+    # num = re.match(r"(\d{2})")
+    # for row in coursenums:
+    #     print(row)
+    # print(coursenums.keys())
+    # keys() and values() will show the respective columns. Adding the full LP string will show the values.
+    # What if... I do something like
+    #      The next step is to compare each of the items in this list with the results of each fname. I wonder if I can do it by regex?
+    lp_dict = {}
+    lp_list = []
+    for fname in glob.glob(directory):
+        readData = pd.read_csv(
+            fname,
+        )
+        emailGroups = readData.groupby(["Email", "Learner Full Name"])[
+            "Course Name"
+        ].nunique()
+        peoples = emailGroups.to_dict()
+        num = re.findall(r"(\d{2})", fname)
+        for lp, nums in coursenums.items():
+            file_num = str(num[0])
+            file_num = f"{file_num:02}"
+            lp_num = re.findall(r"(\d{2})", lp)
+            lp_num = str(lp_num[0])
+            if file_num == lp_num:
+                lp_list = []
+                # print(file_num+"+"+lp_num)
+                for person, completions in peoples.items():
+                    if completions == nums:
+                        lp_list.append(person)
+        ppl_todict = {fname: lp_list}
+        lp_dict.update(ppl_todict)
+
+    final = pd.DataFrame({key: pd.Series(value) for key, value in lp_dict.items()})
+    final.to_csv(
+        "/Users/normrasmussen/Documents/Northpass/Scripts/Skuid_LPs/finaltest3.csv"
+    )
+
+
+if __name__ == "__main__":
+    manualFunc(lpcsv, directory)