def warn_good_import(added, deleted, form, modified):
if deleted.empty and modified.empty:
h.showbox(
"""There are %s rows of new data and no unexpected changes to old data.
Please proceed with <code>data["raw"]</code>.""" %
len(added),
form + ": Importing Data",
"success",
)
h.showdataframe(added)
def show_modified_rows(self):
form, added, deleted, modified = self.form, self.added, self.deleted, self.modified
if not modified.empty:
h.showbox(
"""There are %s rows in the old data that has been modified in the new data.
If this is expected, you can ignore this message.
To further inspect rows type <code>data["modified"]</code>"""
% len(modified),
form + ": Modified",
"danger",
)
h.showdataframe(modified)
def warn_missing(self, missing, form):
if missing.empty:
h.showbox(
"""All patientid's are in New Data.""",
form + ": No Missing Redcap Subjects",
"success",
)
else:
h.showbox(
"""There are %s Redcap subjects missing from the current data."""
% len(missing),
form + ": Redcap Subjects Missing",
"danger",
)
h.showdataframe(missing)
def warn_duplicates(self):
form, added, deleted, modified = self.form, self.added, self.deleted, self.modified
duplicates = df[df.duplicated(['patientid', 'patienttype'],
keep=False)]
duplicates['reason'] = 'Duplicate IDs'
if duplicates.empty:
h.showbox(
"""All patientid + patienttype combos are unique.""",
form + ": No Duplicates",
"success",
)
else:
h.showbox(
"""There are %s rows that contain the same patientid + patienttype."""
% len(duplicates),
form + ": Duplicates",
"danger",
)
h.showdataframe(duplicates)
def warn_not_in_redcap(not_in_redcap, form):
not_in_redcap = h.difference(df, studyids.subject).copy()
not_in_redcap['reason'] = 'PatientID not in Redcap'
not_in_redcap.rename(columns={'sitename': 'site'}, inplace=True)
if not_in_redcap.empty:
h.showbox(
"""All patientid's are in Redcap.""",
form + ": No Subject Missing from Redcap",
"success",
)
else:
h.showbox(
"""There are %s rows with patientid missing from Redcap.""" %
len(not_in_redcap),
form + ": Subjects Missing from Redcap",
"danger",
)
h.showdataframe(not_in_redcap)