import pandas as pd
from lib_cinci import data_folder
import os
path_to_data_folder = data_folder.for_file(__file__)
os.chdir(os.path.join(path_to_data_folder, 'tmp'))
print 'Working in folder: {}'.format(path_to_data_folder)
#Load csv file, parse DATE column
df = pd.read_csv("fire.csv", parse_dates=['incident_date'])
print 'Raw file has {:,d} rows and {:,d} columns'.format(*df.shape)
#Lowercase column names
df.columns = df.columns.map(lambda s: s.lower())
df.rename(columns={'street_address': 'address'}, inplace=True)
#Check how many rows have empty addresses
print '{:,d} rows with empty address, removing those'.format(df.address.isnull().sum())
#Remove rows without address
df = df[df.address.notnull()]
#Check for duplicates
duplicates = df.duplicated()
n_duplicates = duplicates.sum()
print 'Found {:,d} duplicates, dropping them'.format(n_duplicates)
df = df[~duplicates]
#Strip some columns
#csvsql has a bug that is not producing the
year = int(sys.argv[2])
# Set folder where this file is located as working direcory
script_dir = os.path.abspath(os.path.dirname(__file__))
os.chdir(script_dir)
print "Loading definitions.yaml from: %s" % os.getcwd()
with open("definitions.yaml") as f:
definitions = yaml.load(f.read())
names = definitions["names"][year]
# Move current directory do all I/O operations take place in the corresponding
# Data folder
data_folder = data_folder.for_file(__file__)
os.chdir(data_folder)
print "Changing working dir to: %s" % os.getcwd()
# Create tmp file if it does not exist
if not os.path.exists("tmp"):
print "Creating tmp folder in %s" % os.getcwd()
os.makedirs("tmp")
print "Loading data from %d..." % year
# Force all columns to be read as strings to prevent pandas elminating leading 0s
# and other weird stuff. The are some columns with only one blank space, interpret those
# as NA
df = pd.read_csv(input_file, names=names, dtype=np.str, na_values=[" "])
import pandas as pd
from lib_cinci import data_folder
import os
import sys
path_to_data_folder = data_folder.for_file(__file__)
os.chdir(os.path.join(path_to_data_folder, 'tmp'))
print 'Working in folder: %s' % path_to_data_folder
input_filename = "diff_crime.csv"
output_filename = "diff_crime_clean.csv"
#Load csv file
df = pd.read_csv(input_filename, dtype=object)
print 'Raw file has {:,d} rows and {:,d} columns'.format(*df.shape)
#Lowercase column names
df.columns = df.columns.map(lambda s: s.lower())
df['occurredon'] = pd.to_datetime(df['occurredon'])
df = df.set_index('occurredon')
#Rename some columns
mapping = {'location': 'address', 'addressstate': 'state'}
df.index.rename('occurred_on', inplace=True)
df.rename(columns=mapping, inplace=True)
#We are only using data starting from 2012
df = df[df.index.year >= 2012]
print 'Subset from 2012 has {:,d} rows and {:,d} columns'.format(*df.shape)
import os
import pandas as pd
from lib_cinci import data_folder
#Move current directory do all I/O operations take place in the corresponding
#Data folder
data_folder = data_folder.for_file(__file__)
os.chdir(data_folder)
#Create tmp file if it does not exist
if not os.path.exists('tmp'):
print('Creating tmp folder in %s' % os.getcwd())
os.makedirs('tmp')
#Move to tmp folder
os.chdir('tmp')
print('Changing working dir to: %s' % os.getcwd())
def read_for_year(year):
df = pd.read_csv("owners_{}_resolved.csv".format(year))
df["parcel_id"] = df["parcel_id"].astype(str)
#dupes = df.groupby(level=0).filter(lambda x: len(x) > 1)
df = df.drop_duplicates(subset='parcel_id')
df = df.set_index("parcel_id")
entities = df["entity"]
entities.name = "owner_" + str(year)
#Step zero: read from yaml file
parser = argparse.ArgumentParser()
parser.add_argument("update_file",
help="Path to yaml file with configuration parameters")
args = parser.parse_args()
with open(args.update_file, 'r') as f:
params = yaml.load(f)
db_column = params['storage']['column']
file_column = params['source']['column']
schema = params['storage']['schema']
#Folder to use for I/O
folder = data_folder.for_file(args.update_file)
os.chdir(folder)
logger.info('Using {} for I/O operations'.format(folder))
#Step one: download file from remote server if user provided url
try:
url = params['source']['url']
except Exception, e:
logger.info('URL was not present in the configuration file...')
else:
logger.info('Downloading file...'.format(folder))
data_file = urllib2.urlopen(url)
#Dowload file replacing it if already exists
with open(params['source']['filename'], 'wb') as output:
output.write(data_file.read())
logger = logging.getLogger()
#Step zero: read from yaml file
parser = argparse.ArgumentParser()
parser.add_argument("update_file", help="Path to yaml file with configuration parameters")
args = parser.parse_args()
with open(args.update_file, 'r') as f:
params = yaml.load(f)
db_column = params['storage']['column']
file_column = params['source']['column']
schema = params['storage']['schema']
#Folder to use for I/O
folder = data_folder.for_file(args.update_file)
os.chdir(folder)
logger.info('Using {} for I/O operations'.format(folder))
#Step one: download file from remote server if user provided url
try:
url = params['source']['url']
except Exception, e:
logger.info('URL was not present in the configuration file...')
else:
logger.info('Downloading file...'.format(folder))
data_file = urllib2.urlopen(url)
#Dowload file replacing it if already exists
with open(params['source']['filename'],'wb') as output:
output.write(data_file.read())