Zin Yosrim zinyosrim

## triangle_df.py
import numpy as np
import pandas as pd

N = 20
rand_matrix = np.asarray([random.randrange(1,11)/10 for _ in range(1, N*N+1) ]).reshape(N,N)
data = np.flip(np.triu(rand_matrix), 1)
df = pd.DataFrame(data, index=pd.date_range(start='2015-01-01', freq='MS', periods=N),\
                  columns = range(1,N+1))
df[1]=1

## ga_number_to_spreadsheet_number.txt
=VALUE(REGEXREPLACE(REGEXEXTRACT(C8;"€([0-9]*\,[0-9]+[0-9]+)");",";""))

## pandas_pretty_print_full.py
import pprint
def pprint_full(x):
    pd.set_option('display.max_rows', len(x))
    pd.set_option('display.max_columns', None)
    pd.set_option('display.width', 2000)
    pd.set_option('display.float_format', '{:20,.2f}'.format)
    pd.set_option('display.max_colwidth', -1)
    #print(x)
    pprint.pprint(x)
    pd.reset_option('display.max_rows')

## zip_unzip_example.py
seq1 = ['good', 'bad', 'ugly']
seq2 = ['child', 'man', 'woman']
zipped = zip(seq1, seq2)
starzipped = zip(*[seq1, seq2])
for el in starzipped: print(el)

## dict_in_column_to_df_column.py
df = pd.DataFrame({'order_id': ['A', 'B'],
                    'address': [{'city': "NY", 'latitude': 2.12, 'longitude' : 3.12,'country_code' : "US"},
                                {'city': "KL", 'latitude': 12.12, 'longitude' : 23.12,'country_code' : "MY"}]},
                   columns= ['order_id', 'address'])

new_cols = ['city', 'country_code']
for col in new_cols:
    df['address_{}'.format(col)] = df['address'].map(lambda x: np.nan if pd.isnull(x) else x[col])

## sample_dataframes.py
pd.DataFrame({'order_id': ['A', 'B'],
                   'items': [[{'item': 1, 'color': 'blue' },
                              {'item': 2, 'color': 'red'  }],
                             [{'item': 3, 'color': 'green'},
                              {'item': 2, 'color': 'pink' }]]},
                  columns= ['order_id', 'items'])

pd.DataFrame({'order_id': ['A', 'A', 'B', 'B'],
              'product_id': [1, 2, 3, 2],
              'product_color': ['blue', 'red', 'green', 'pink'] },

## komponenten.csv

          
            Komponente
            Kurzbeschreibung
            Argumente dafür
            Kosten

            
              MailChimp
              Sehr verbreitetes Newsletter-Versand-System
              Gute Integration mit anderen Systemen. Großer Funktionsumfang
              Kostenloser Plan verfügbar

            
              MailMunch
              Shopify App für automatische Pop-up's
              granulare Einstellmöglichkeiten für Pop-up's
              Kostenloser Plan verfügbar. Nächste Stufe ab 12$/Monat

            
              Coupon Carrier
              Shopify App für das Weiterreichen von Gutschein-Codes an Mailchimp
              Leicht zu bedienen
              Verbrauchsabhängige Kosten im Cent Bereich pro versendeten Code

            
              Bulk Discounts
              Shopify App für Gutschein-Codes
              leichtes Erzeugen einer großen Anzahl von Gutscheinen
              Kostenloser Plan verfügbar

## import_grouped_data.py
import csv

reader = csv.reader(open('products.csv'))
products_list = []
first_of_group = ""

for row in reader:
    product_name, feature1, feature2 = row
    product_dict = {}


## convertCurrencyToNumber.txt
=value(regexreplace(regexreplace(REGEXREPLACE(B19;"€"; ""); ",";"");"\.";","))

## generate_pandas_dataframe_with_random_integers.py
import pandas as pd
import numpy as np
from random import randint
df = pd.DataFrame(np.random.randint(0,10,size=(10, 3)), columns=list('ABC'), index=range(1,11))
	import numpy as np
	import pandas as pd

	N = 20
	rand_matrix = np.asarray([random.randrange(1,11)/10 for _ in range(1, N*N+1) ]).reshape(N,N)
	data = np.flip(np.triu(rand_matrix), 1)
	df = pd.DataFrame(data, index=pd.date_range(start='2015-01-01', freq='MS', periods=N),\
	columns = range(1,N+1))
	df[1]=1
	import pprint
	def pprint_full(x):
	pd.set_option('display.max_rows', len(x))
	pd.set_option('display.max_columns', None)
	pd.set_option('display.width', 2000)
	pd.set_option('display.float_format', '{:20,.2f}'.format)
	pd.set_option('display.max_colwidth', -1)
	#print(x)
	pprint.pprint(x)
	pd.reset_option('display.max_rows')
	seq1 = ['good', 'bad', 'ugly']
	seq2 = ['child', 'man', 'woman']
	zipped = zip(seq1, seq2)
	starzipped = zip(*[seq1, seq2])
	for el in starzipped: print(el)
	df = pd.DataFrame({'order_id': ['A', 'B'],
	'address': [{'city': "NY", 'latitude': 2.12, 'longitude' : 3.12,'country_code' : "US"},
	{'city': "KL", 'latitude': 12.12, 'longitude' : 23.12,'country_code' : "MY"}]},
	columns= ['order_id', 'address'])

	new_cols = ['city', 'country_code']
	for col in new_cols:
	df['address_{}'.format(col)] = df['address'].map(lambda x: np.nan if pd.isnull(x) else x[col])
	pd.DataFrame({'order_id': ['A', 'B'],
	'items': [[{'item': 1, 'color': 'blue' },
	{'item': 2, 'color': 'red' }],
	[{'item': 3, 'color': 'green'},
	{'item': 2, 'color': 'pink' }]]},
	columns= ['order_id', 'items'])

	pd.DataFrame({'order_id': ['A', 'A', 'B', 'B'],
	'product_id': [1, 2, 3, 2],
	'product_color': ['blue', 'red', 'green', 'pink'] },
Komponente	Kurzbeschreibung	Argumente dafür	Kosten
MailChimp	Sehr verbreitetes Newsletter-Versand-System	Gute Integration mit anderen Systemen. Großer Funktionsumfang	Kostenloser Plan verfügbar
MailMunch	Shopify App für automatische Pop-up's	granulare Einstellmöglichkeiten für Pop-up's	Kostenloser Plan verfügbar. Nächste Stufe ab 12$/Monat
Coupon Carrier	Shopify App für das Weiterreichen von Gutschein-Codes an Mailchimp	Leicht zu bedienen	Verbrauchsabhängige Kosten im Cent Bereich pro versendeten Code
Bulk Discounts	Shopify App für Gutschein-Codes	leichtes Erzeugen einer großen Anzahl von Gutscheinen	Kostenloser Plan verfügbar
	import csv

	reader = csv.reader(open('products.csv'))
	products_list = []
	first_of_group = ""

	for row in reader:
	product_name, feature1, feature2 = row
	product_dict = {}
	import pandas as pd
	import numpy as np
	from random import randint
	df = pd.DataFrame(np.random.randint(0,10,size=(10, 3)), columns=list('ABC'), index=range(1,11))