Pranjal Saxena pranjalAI

## tip1.py
from collections import Counter
mylst = [1,1,1,2,2,2,2,3,3,3,3,3,4,4,5,6,6,6]
print(Counter(mylst))

## data_info.py
Total_transactions = len(data)
normal = len(data[data.Class == 0])
fraudulent = len(data[data.Class == 1])
fraud_percentage = round(fraudulent/normal*100, 2)
print(cl('Total number of Trnsactions are {}'.format(Total_transactions), attrs = ['bold']))
print(cl('Number of Normal Transactions are {}'.format(normal), attrs = ['bold']))
print(cl('Number of fraudulent Transactions are {}'.format(fraudulent), attrs = ['bold']))
print(cl('Percentage of fraud Transactions is {}'.format(fraud_percentage), attrs = ['bold']))

## libraries.py
#Packages related to general operating system & warnings
import os
import warnings
warnings.filterwarnings('ignore')
#Packages related to data importing, manipulation, exploratory data #analysis, data understanding
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from termcolor import colored as cl # text customization
#Packages related to data visualizaiton

## mahotas.py
import mahotas
import mahotas.demos
import numpy as np
from pylab import imshow, gray, show
from os import path
photo = mahotas.demos.load('luispedro', as_grey=True)
photo = photo.astype(np.uint8)
gray()
imshow(photo)
show()

## OpenCV_Blur.py
resp = ur.urlopen("https://thumbor.forbes.com/thumbor/960x0/https%3A%2F%2Fspecials-images.forbesimg.com%2Fdam%2Fimageserve%2F1068867780%2F960x0.jpg%3Ffit%3Dscale")
image = np.asarray(bytearray(resp.read()), dtype="uint8")
im = cv2.imdecode(image, cv2.IMREAD_COLOR)
blur = cv2.GaussianBlur(im, (5,5),0)
cv2_imshow(blur)

## bs4.html
html_doc = """
<html>
    <head>
        <title>Test Page</title>
    </head>
    <body>
        <p><b>This is a test page.</b></p>
    </body>
</html>
"""

## Yara.py
import yara

rule = yara.compile(source='rule foo: bar {strings: $a = "lmn" condition: $a}')
matches = rule.match(data='abcdefgjiklmnoprstuvwxyz')

## Missingno.py
import pandas as pd
import missingno as msno
dataset = pd.read_csv('filename.csv')
msno.bar(dataset)

## altair.py
import altair as alt
from vega_datasets import data
iris = data.iris()

# Making the Scatter Plot with altair
alt.Chart(iris).mark_point().encode(
    # defining x-axis
    x='sepalLength',
    # defining y-axis
    y='petalLength',

## plotly.py
import plotly.graph_objects as go
fig = go.figure(data = go.bar(y=[1,2,3]))
fig.show()
	from collections import Counter
	mylst = [1,1,1,2,2,2,2,3,3,3,3,3,4,4,5,6,6,6]
	print(Counter(mylst))
	Total_transactions = len(data)
	normal = len(data[data.Class == 0])
	fraudulent = len(data[data.Class == 1])
	fraud_percentage = round(fraudulent/normal*100, 2)
	print(cl('Total number of Trnsactions are {}'.format(Total_transactions), attrs = ['bold']))
	print(cl('Number of Normal Transactions are {}'.format(normal), attrs = ['bold']))
	print(cl('Number of fraudulent Transactions are {}'.format(fraudulent), attrs = ['bold']))
	print(cl('Percentage of fraud Transactions is {}'.format(fraud_percentage), attrs = ['bold']))
	#Packages related to general operating system & warnings
	import os
	import warnings
	warnings.filterwarnings('ignore')
	#Packages related to data importing, manipulation, exploratory data #analysis, data understanding
	import numpy as np
	import pandas as pd
	from pandas import Series, DataFrame
	from termcolor import colored as cl # text customization
	#Packages related to data visualizaiton
	import mahotas
	import mahotas.demos
	import numpy as np
	from pylab import imshow, gray, show
	from os import path
	photo = mahotas.demos.load('luispedro', as_grey=True)
	photo = photo.astype(np.uint8)
	gray()
	imshow(photo)
	show()
	resp = ur.urlopen("https://thumbor.forbes.com/thumbor/960x0/https%3A%2F%2Fspecials-images.forbesimg.com%2Fdam%2Fimageserve%2F1068867780%2F960x0.jpg%3Ffit%3Dscale")
	image = np.asarray(bytearray(resp.read()), dtype="uint8")
	im = cv2.imdecode(image, cv2.IMREAD_COLOR)
	blur = cv2.GaussianBlur(im, (5,5),0)
	cv2_imshow(blur)
	html_doc = """
	<html>
	<head>
	<title>Test Page</title>
	</head>
	<body>
	<p><b>This is a test page.</b></p>
	</body>
	</html>
	"""
	import yara

	rule = yara.compile(source='rule foo: bar {strings: $a = "lmn" condition: $a}')
	matches = rule.match(data='abcdefgjiklmnoprstuvwxyz')
	import pandas as pd
	import missingno as msno
	dataset = pd.read_csv('filename.csv')
	msno.bar(dataset)
	import altair as alt
	from vega_datasets import data
	iris = data.iris()

	# Making the Scatter Plot with altair
	alt.Chart(iris).mark_point().encode(
	# defining x-axis
	x='sepalLength',
	# defining y-axis
	y='petalLength',
	import plotly.graph_objects as go
	fig = go.figure(data = go.bar(y=[1,2,3]))
	fig.show()