collection = utils.get_geography_collection() with open(FILENAME) as f: rows = UnicodeCSVReader(f) headers = rows.next() updates = 0 row_count = 0 for row in rows: row_count += 1 row_dict = dict(zip(headers, row)) xref = utils.xref_from_row_dict(row_dict) geography = utils.find_geography_by_xref(collection, xref, fields=['data']) if not geography: continue if YEAR not in geography['data']: geography['data'][YEAR] = {} tables = {} for k, v in row_dict.items(): # Format table names to match labels t = utils.parse_table_from_key(k) if t not in tables: tables[t] = {}
collection = db[config.GEOGRAPHIES_2000_COLLECTION] with open(FILENAME) as f: rows = UnicodeCSVReader(f) headers = rows.next() updates = 0 row_count = 0 for row in rows: row_count += 1 row_dict = dict(zip(headers, row)) xref = utils.xref_from_row_dict(row_dict) geography = utils.find_geography_by_xref(collection, xref) if not geography: continue if YEAR not in geography['data']: geography['data'][YEAR] = {} tables = {} for k, v in row_dict.items(): # Format table names to match labels t = utils.parse_table_from_key(k) if t not in tables: tables[t] = {}
with open(FILENAME) as f: rows = UnicodeCSVReader(f) headers = rows.next() updates = 0 row_count = 0 for row in rows: row_count += 1 row_dict = dict(zip(headers, row)) xref = utils.xref_from_row_dict(row_dict) geography = utils.find_geography_by_xref(collection, xref, fields=['data']) if not geography: continue if YEAR not in geography['data']: geography['data'][YEAR] = {} tables = {} for k, v in row_dict.items(): # Format table names to match labels t = utils.parse_table_from_key(k) if t not in tables: tables[t] = {}
collection = utils.get_geography2000_collection() with open(FILENAME) as f: rows = UnicodeCSVReader(f) headers = rows.next() updates = 0 row_count = 0 for row in rows: row_count += 1 row_dict = dict(zip(headers, row)) xref = utils.xref_from_row_dict(row_dict) geography = utils.find_geography_by_xref(collection, xref) if not geography: continue if YEAR not in geography['data']: geography['data'][YEAR] = {} tables = {} for k, v in row_dict.items(): # Format table names to match labels t = utils.parse_table_from_key(k) if t not in tables: tables[t] = {}