def import_fjc_judges(self, infile=None):
if infile is None:
self.ensure_input_file()
infile = self.options["input_file"]
textfields = [
"First Name",
"Middle Name",
"Last Name",
"Gender",
"Birth City",
"Birth State",
"Death City",
"Death State",
]
df = pd.read_csv(infile)
df = df.replace(r"^\s+$", np.nan, regex=True)
for x in textfields:
df[x] = df[x].replace(np.nan, "", regex=True)
df["Professional Career"].replace(
to_replace=r";\sno", value=r", no", inplace=True, regex=True
)
for i, row in df.iterrows():
if i < self.options["offset"]:
continue
if i >= self.options["limit"] > 0:
break
make_federal_judge(dict(row), testing=self.debug)
def import_fjc_judges(self):
self.ensure_input_file()
textfields = ['firstname', 'midname', 'lastname', 'gender',
'Place of Birth (City)', 'Place of Birth (State)',
'Place of Death (City)', 'Place of Death (State)']
df = pd.read_excel(self.options['input_file'], 0)
for x in textfields:
df[x] = df[x].replace(np.nan, '', regex=True)
for i, row in df.iterrows():
make_federal_judge(dict(row), testing=self.debug)
def import_fjc_judges(self):
self.ensure_input_file()
textfields = [
'firstname', 'midname', 'lastname', 'gender',
'Place of Birth (City)', 'Place of Birth (State)',
'Place of Death (City)', 'Place of Death (State)'
]
df = pd.read_excel(self.options['input_file'], 0)
for x in textfields:
df[x] = df[x].replace(np.nan, '', regex=True)
for i, row in df.iterrows():
make_federal_judge(dict(row), testing=self.debug)
def import_fjc_judges(self,infile=None):
if infile is None:
self.ensure_input_file()
infile = self.options['input_file']
textfields = ['firstname', 'midname', 'lastname', 'gender',
'Place of Birth (City)', 'Place of Birth (State)',
'Place of Death (City)', 'Place of Death (State)']
df = pd.read_excel(infile, 0)
for x in textfields:
df[x] = df[x].replace(np.nan, '', regex=True)
df['Employment text field'].replace(to_replace=r';\sno', value=r', no', inplace = True, regex = True)
for i, row in df.iterrows():
make_federal_judge(dict(row), testing=self.debug)
def import_fjc_judges(self, infile=None):
if infile is None:
self.ensure_input_file()
infile = self.options['input_file']
textfields = ['firstname', 'midname', 'lastname', 'gender',
'Place of Birth (City)', 'Place of Birth (State)',
'Place of Death (City)', 'Place of Death (State)']
df = pd.read_excel(infile, 0)
for x in textfields:
df[x] = df[x].replace(np.nan, '', regex=True)
df['Employment text field'].replace(to_replace=r';\sno', value=r', no',
inplace=True, regex=True)
for i, row in df.iterrows():
make_federal_judge(dict(row), testing=self.debug)
def import_fjc_judges(self, infile=None):
if infile is None:
self.ensure_input_file()
infile = self.options['input_file']
textfields = ['First Name', 'Middle Name', 'Last Name', 'Gender',
'Birth City', 'Birth State',
'Death City', 'Death State']
df = pd.read_csv(infile)
df = df.replace(r'^\s+$', np.nan, regex=True)
for x in textfields:
df[x] = df[x].replace(np.nan, '', regex=True)
df['Professional Career'].replace(to_replace=r';\sno', value=r', no',
inplace=True, regex=True)
for i, row in df.iterrows():
if i < self.options['offset']:
continue
if i >= self.options['limit'] > 0:
break
make_federal_judge(dict(row), testing=self.debug)
