Skip to main content

To find a maximum number from a list, then finding the length of that maximum number and the total number of elements in the list using python.



  1. Now this is how we can find the maximum number from the list.
  2. Length of the maximum number from the list.
  3. The total number of elements from the list.



a = [54654,854,21,715732143241974,871,6354,9753,21]
print('the maximum number from the list is:', max(a))


def digits(a):
count = 0
while a != 0:
count+=1
a=a//10
return count
print('length of the maximum number from the list is:', digits(max(a)))

print('the total number of elements in the list are:', len(a))

Comments

Popular posts from this blog

Stock Market using Python

 "The stock market is a device for transferring money from the impatient to the patient." - Warren Buffett Today we'll look into few ways for accessing the stock market. And we'll do this using Python ! Now, as we know that there are 2 stock exchange in India; BSE and NSE So we'll get the data from both! To begin with let's access the data from BSE first. (P.S: I certainly like the 2nd and the 3rd method to access stock market!) * So, to import the BSE data we need to " pip install bsedata ". => And then import the module, => Create an object to store the Driver Class => Then we need to do " getQuote('script_code')" where we need to provide a script code of a company which we need to access. Just like here we have given; => And from here we can see that the script code was for the company named "V-MART". But we can't remember all the script code hence we need to download this script file from the BSE websi

Predicting whether the bank will give loan to its customers based on their credit score (Logistic Regression)

"The best thing about data is that it tells a story." - Naveen Jain Today let's have a look at another machine learning model know as Logistic Regression. Logistic Regression is a statistical model where the outcome is predicted as binary such as YES or NO, based on the previous/train_dataset. ( Please open the images in a new tab or try to zoom-in ) import required models read your dataframe visualize your dataset create Logistic Regression model split your data into train and test dataset fit your train dataset into the regression model predict future values visualize your predicted values Github link for pdf:  click here

Glowing Border effect using html/css

  {html code} <html>     <head>         <link href='E:\html\.vscode\.vscode\style.css' type='text/css' rel='stylesheet'>         <title>Glowing Border</title>     </head>     <body>         <div class='box'>             <div class='text'>             <h2><u>Glowing Border</u></h2>             <p>HTML and CSS are technically not the programming languages, they are the scripting languages.              Usually used for the front-end development.</p>             </div>         </div>             </body> </html> {css code} body{     background: black;     display: flex; } .text{     padding: 30px;     margin: 10px;     letter-spacing: 1px;     box-sizing: border-box;     color: white; } .box{     top: 20%;     left: 40%;     display: flex;     position: relative;     width: 300px;     height: 420px;     justify-items: center;     align-it