Keeping Pandas DataFrames clean when importing JSON

basic.py

from pandas.io.json import json_normalize
df = json_normalize(data)

data-frame-from-dict.py

class DataFrameFromDict(object):
    """
    Temporarily imports data frame columns and deletes them afterwards.
    """
    def __init__(self, data):
        self.df = json_normalize(data)
        self.columns = list(self.df.columns.values)
    def __enter__(self):
        return self.df
    def __exit__(self, exc_type, exc_val, exc_tb):
        self.df.drop([c for c in self.columns], axis=1, inplace=True)

dropping-or-selecting-afterwards.py

from pandas.io.json import json_normalize
df = json_normalize(data)

// make temporary columns
df.columns = ['temp_' + c for c in df.columns]

// pre-processing, basic calculations, etc.
df['company_id'] = df['temp_companyId']
df['location'] = df['temp_properties.city.value']
df['name'] = df['temp_properties.name.value']
df['domain'] = df['temp_properties.website.value']
//... .apply(), .as_type(int), whatever...

df.drop([c for c in df.columns if c.startswith('temp_')], axis=1, inplace=True)
// or
df = df[[c for c in df.columns if not c.startswith('temp_')]]

keeping-columns.py

from pandas.io.json import json_normalize

df = json_normalize(data)

df['company_id'] = df['companyId']
df['location'] = df['properties.city.value']
df['name'] = df['properties.name.value']
df['domain'] = df['properties.website.value']
//... .apply(), .as_type(int), whatever...

with-context-manager.py

with DataFrameFromDict(companies) as df:
    // imported dict now in df, same result as json_normalize
    df['company_id'] = df['companyId']
    df['location'] = df['properties.city.value']
    df['name'] = df['properties.name.value']
    df['domain'] = df['properties.website.value']
// after context exits, df contains company_id, location, name, and domain
// but no more temporary columns
print(df)