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from skimage import data, io import sys from skimage.color import gray2rgb try:     rgb_image = data.imread(sys.argv[1])     height = rgb_image.shape[0]     width = rgb_image.shape[1]     if(len(rgb_image.shape) < 3):         rgb_image = gray2rgb(rgb_image)         for i,j in zip(range(int(width/8)), range(int(width/8),0,-1)):         rgb_image[i, 0:j, :] = 0         for i,j in zip(range(int(7*(height/8)),height), range(0,int(width/8))):         rgb_image[i, 0:j, :] = 0    

from skimage import data, io import sys from skimage.color import gray2rgb try:     rgb_image = data.imread(sys.argv[1])     height = rgb_image.shape[0]     width = rgb_image.shape[1]     if height == width:         print("already square image")         else:         if(len(rgb_image.shape) < 3):             rgb_image = gray2rgb(rgb_image)                     right_image = rgb_image.copy()         left_image = rgb_image.copy()         center_image = rgb_image.copy()        

from skimage import data, io import random import sys from skimage.color import gray2rgb try:     rgb_image = data.imread(sys.argv[1])     height = rgb_image.shape[0]     width = rgb_image.shape[1]     if(len(rgb_image.shape) < 3):         rgb_image = gray2rgb(rgb_image)         for i in range(height):         for j in range(width):             for k in range(rgb_image.shape[2]):

Code: from skimage import data, io, util import random import sys from skimage.color import rgb2gray try:     rgb_image = data.imread(sys.argv[1])         height = rgb_image.shape[0]     width = rgb_image.shape[1]         if(len(rgb_image.shape) == 3):         rgb_image = util.img_as_ubyte(rgb2gray(rgb_image))

1. Histogram >>> mylist = [1,3,2,5,4,4,2,2,4,2,4,2,4,6,4,5,2] >>> import matplotlib.pyplot as plt >>> plt.hist(mylist) (array([ 1.,  0.,  6.,  0.,  1.,  0.,  6.,  0.,  2.,  1.]), array([ 1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5,  5. ,  5.5,  6. ]), <a list of 10 Patch objects>) >>> plt.show()

Code:- from skimage import data, io import random try:     rgb_image = data.imread("Collage.jpg")     #print(rgb_image.shape)         red_image = rgb_image.copy()     green_image = rgb_image.copy()     blue_image = rgb_image.copy()         red_image[:, :, (1, 2)] = 0     io.imsave("red_output_image.jpg", red_image)         green_image[:, :, (0, 2)] = 0     io.imsave("green_output_image.jpg", green_image)         blue_image[:, :, (0, 1)] = 0     io.imsave("blue_output_image.jpg", blue_image)    

import pandas as pd from collections import Counter from datetime import datetime, timedelta from bokeh.charts import Bar, output_file, show from bokeh.models.layouts import Column import numpy as np try:     data = pd.read_csv('new.csv')     scan_col = Counter(data['Scan'])     values = list()     keys = list()         for s in scan_col.keys():         scan_time_total = datetime.strptime("00:00:00","%H:%M:%S")         scan_time_total = timedelta(hours=scan_time_total.hour, minutes=scan_time_total.minute, seconds=scan_time_total.second)

import pandas as pd from collections import Counter from datetime import datetime, timedelta import matplotlib.pyplot as plt; plt.rcdefaults() import numpy as np import matplotlib.pyplot as plt try:     data = pd.read_csv('new.csv')     srn_col = Counter(data['SRN'])     month_col = Counter(data['Month'])     scan_col = Counter(data['Scan'])     scan_dict = {}

Step 1: Install plotly package if you haven't. Follow this article: http://com.puter.tips/2017/02/install-plotly-package-in-python.html Step 2: Set up your online credentials for plotly account. 2.1: Go to https://plot.ly/settings/api 2.2: Sign in/sign up. 2.3: Open https://plot.ly/settings/api (API Settings page) and click on Regenerate Key button. Copy the API key.

You need pip package manager to install Plotly package in Python. Use this command to install plotly with python: pip install plotly Ref.: https://plot.ly/python/getting-started/ Plotly is a library for building interactive charts in Python that render in the browser, with hover, zoom, and pan built in. Installing it is a single pip command, as shown above. Once installed you can create figures with plotly.express or plotly.graph_objects and export them to HTML or images. It works well inside Jupyter notebooks and dashboards.