def main():
#Define our connection string
csv_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/'
current_parameter_checked = 'linking'
magasin_to_display = ''
conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'"
# print the connection string we will use to connect
print "Connecting to database\n ->%s" % (conn_string)
# get a connection, if a connect cannot be made an exception will be raised here
conn = psycopg2.connect(conn_string)
# conn.cursor will return a cursor object, you can use this cursor to perform queries
cursor = conn.cursor()
# execute our Query
# X = np.asarray(predictors_list);
my_linking_counter_request = "select distinct counter, count(*) from CDS_LINKING_SIMILAR_PRODUCTS group by counter order by counter asc"
print "Executing the following request to fetch data for all magasins : " + my_linking_counter_request
# fetching data to display for magasin Musique
cursor.execute(my_linking_counter_request);
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,csv_saving_path)
def main():
#Define our connection string
results_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/'
magasin_to_display = ''
conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'"
# print the connection string we will use to connect
print "Connecting to database\n ->%s" % (conn_string)
# get a connection, if a connect cannot be made an exception will be raised here
conn = psycopg2.connect(conn_string)
# conn.cursor will return a cursor object, you can use this cursor to perform queries
cursor = conn.cursor()
my_full_request = "select nb_distinct_cat5, nb_distinct_cat4, nb_distinct_brand_without_default, nb_distinct_vendor, nb_distinct_magasin, nb_distinct_state from CATALOG where magasin=(%s)"
dataNames=["Category5","Category4","Brand","Vendor","Magasin","State"];
print "Data fetched : "+ ', '.join(dataNames)
# execute our Query
# X = np.asarray(predictors_list);
my_brand_request = "select distinct nb_distinct_brand, count(*) from CATALOG where nb_distinct_brand is not null group by nb_distinct_brand order by nb_distinct_brand asc"
print "Executing the following request to fetch data for all magasins : " + my_brand_request
current_parameter_checked="distinct_brand"
# fetching data to display for magasin Musique
cursor.execute(my_brand_request);
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_magasin_request = "select distinct nb_distinct_magasin, count(*) from CATALOG where nb_distinct_magasin is not null group by nb_distinct_magasin order by nb_distinct_magasin asc"
print "Executing the following request to fetch data for magasins : " + my_magasin_request
current_parameter_checked="distinct_magasin"
# fetching data to display for magasin Musique
cursor.execute(my_magasin_request);
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_state_request = "select distinct nb_distinct_state, count(*) from CATALOG where nb_distinct_state is not null group by nb_distinct_state order by nb_distinct_state asc"
print "Executing the following request to fetch data for magasins : " + my_state_request
current_parameter_checked="distinct_state"
# fetching data to display for magasin Musique
cursor.execute(my_state_request);
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_cat4_request = "select distinct nb_distinct_cat4, count(*) from CATALOG where nb_distinct_cat4 is not null group by nb_distinct_cat4 order by nb_distinct_cat4 asc"
print "Executing the following request to fetch data for magasins : "+ my_cat4_request
current_parameter_checked="distinct_cat4"
# fetching data to display for magasin Musique
cursor.execute(my_cat4_request);
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
def main():
#Define our connection string
results_saving_path = '/home/sduprey/My_Data/My_Kriter_Data/My_Kriter_Results/'
conn_string = "host='localhost' dbname='KRITERDB' user='******' password='******'"
# print the connection string we will use to connect
print "Connecting to database\n ->%s" % (conn_string)
# get a connection, if a connect cannot be made an exception will be raised here
conn = psycopg2.connect(conn_string)
# conn.cursor will return a cursor object, you can use this cursor to perform queries
cursor = conn.cursor()
my_distinct_magasin_request = "select distinct magasin from CATALOG"
cursor.execute(my_distinct_magasin_request);
# retrieve the records from the database
datas = cursor.fetchall()
my_magasins = [item[0] for item in datas];
current_parameter_checked="";
#my_magasins = ["Musique","Librairie"];
for magasin_to_loop in my_magasins:
magasin_to_display=magasin_to_loop.replace (" ", "_")
my_brand_request = "select distinct nb_distinct_brand, count(*) from CATALOG where nb_distinct_brand is not null and magasin=(%s) group by nb_distinct_brand order by nb_distinct_brand asc"
current_parameter_checked="distinct_brand"
print "Dealing with :"+current_parameter_checked
print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_brand_request
# fetching data to display for magasin Musique
cursor.execute(my_brand_request,(magasin_to_loop,));
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
print X.dtype
print X.size
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_magasin_request = "select distinct nb_distinct_magasin, count(*) from CATALOG where nb_distinct_magasin is not null and magasin=(%s) group by nb_distinct_magasin order by nb_distinct_magasin asc"
current_parameter_checked="distinct_magasin"
print "Dealing with :"+current_parameter_checked
print "Executing the following request to fetch data for magasins : " +magasin_to_loop+ my_magasin_request
# fetching data to display for magasin Musique
cursor.execute(my_magasin_request,(magasin_to_loop,));
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_state_request = "select distinct nb_distinct_state, count(*) from CATALOG where nb_distinct_state is not null and magasin=(%s) group by nb_distinct_state order by nb_distinct_state asc"
current_parameter_checked="distinct_state"
print "Dealing with :"+current_parameter_checked
print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_state_request
# fetching data to display for magasin Musique
cursor.execute(my_state_request,(magasin_to_loop,));
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
my_cat4_request = "select distinct nb_distinct_cat4, count(*) from CATALOG where nb_distinct_cat4 is not null and magasin=(%s) group by nb_distinct_cat4 order by nb_distinct_cat4 asc"
current_parameter_checked="distinct_category_level_4"
print "Dealing with :"+current_parameter_checked
print "Executing the following request to fetch data for magasins : "+magasin_to_loop + my_cat4_request
# fetching data to display for magasin Musique
cursor.execute(my_cat4_request,(magasin_to_loop,));
# retrieve the records from the database
numerical_data = cursor.fetchall()
X= np.asanyarray(numerical_data);
#y= np.asanyarray(y);
print type(X)
print X.shape
save_histogram_as_csv_file(current_parameter_checked, magasin_to_display,X,results_saving_path)
