Akramz

import pandas as pd 
import numpy as np 
from sys import exit

data = pd.read_csv('../../data/train.csv', sep=',')
train = data[['Address']]

train = train.loc[train['Address'].str.contains(' Block of ')]
train['count'] = 1
train = train.groupby('Address').sum().reset_index()

Akramz

import pandas as pd 
import numpy as np 

data = pd.read_csv('../../data/train.csv', sep=',')
train = data[['PdDistrict']]
train['count'] = 1
train = train.groupby('PdDistrict').sum().reset_index()
print train

Akramz

import pandas as pd
import numpy as np
import zipfile
import matplotlib.pyplot as pl
import seaborn as sns
from sys import exit

mapdata = np.loadtxt("../data/sf_map_copyright_openstreetmap_contributors.txt")
asp = mapdata.shape[0] * 1.0 / mapdata.shape[1]

Akramz

import pandas as pd 
import numpy as np
import matplotlib.pyplot as plt
from sys import exit

data = pd.read_csv('../data/locations/0.csv', sep = ',')

xyData = data[['X', 'Y', 'Category']]

allList = [

Akramz

import pandas as pd 
import numpy as np 
from matplotlib import pyplot as plt
import seaborn as sns
from sys import exit

def cut(num):
	if num < 10:
		return 5
	elif num < 20:

Akramz

import pandas as pd 
import numpy as np 
from sys import exit 
from sklearn import cross_validation
from sklearn import datasets
from sklearn import svm
from sklearn.naive_bayes import GaussianNB

data = pd.read_csv('../../data/improv/train1.csv')

Akramz

import pandas as pd 
from sys import exit
import numpy as np 

data = pd.read_csv('../../train.csv')
data = data[['Survived', 'Pclass', 'Sex', 'SibSp', 'Parch', 'Embarked']].dropna()

# male = 0
# female = 1
# S = 0

Akramz

import pandas as pd
data = pd.read_csv('../data/train.csv', sep=',')
print data[(~data['Address'].str.contains(" Block of ")) & (~data['Address'].str.contains(" / "))].Address

Akramz

#CONDOR_HOST = reynolds-master.reynol.dz
#
#COLLECTOR_NAME = TEFPL at $(FULL_HOSTNAME))
#START = $(CS_START)
#SUSPEND = $(CS_SUSPEND)
#CONTINUE = $(CS_CONTINUE)
#PREEMPT = $(CS_PREEMPT)
#KILL = $(CS_KILL)
#
#DAEMON_LIST = MASTER, SCHEDD, STARTD

Akramz

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.api as sm
import sys

# try whatever you want
element = 'hour'

df = pd.read_csv('../improved_data_set/turnstile_weather_v2.csv', index_col=0)