How to remove special character like  using Python?

In this blog post I am going to share you an Python function which can be used to remove special character in your data. It is normal that you will get special character like Ä, NÄ�sÄ«f etc when scrape from website. This will cause trouble when you want to export the data and it also doesn't looks good. Below code helps us to solve the problem:

def cleanup(value):
return value.encode('ascii', errors='replace').replace("?"," ")

You can run the above funtion in Pandas to column which got the special character. Below is one sample:

data['Name']= data['Name'].apply(cleanup)

In above line data is the data frame and it has column named as Name. I am using apply function to run my custom code which will replace the any weird character to blanks.

You can covert any column to numeric using below line:

data['Age'] = data['Age'].apply(pd.to_numeric, errors='coerce')

Again in above line I am using apply function but this …

Pandas create new column based on existing column

In SQL, we can just use SELECT statement to create a new column. In Python, we can do the same using the Pandas. For using Pandas, first create a custom function for how you need the new column to be created.

I had an scenario where I have to classify the person as Adult or Child. For this purpose I will be using the Age column in my data-set. If the age is above 18 and I will create the corresponding value as Adult in my new column. So let's see how this can be achieved.

def checkAdult(age):
    if age>=18:
        return Adult
        return Child

Above is my custom function. Where it takes one argument age and returns Adult or child.

The above Python function can be used in the existing data frame (data) to create new column(Adult/Child).


I am creating new column with name Adult/Child. I am passing Age column to the checkAdult function as define in the right hand side.

Easy method to scrape html table using Python

Scrapping table can be sometimes quite annoying to do. I have worked on more than 50+ scrapping projects to scrape the html tables. Here is the best and easiest way that will work with any website. For this purpose I will be using Beautiful Soup and Pandas.

datafile=<YOUR HTML PAGE>

from bs4 import BeautifulSoup
with open(datafile,"r") as f:
    soup = BeautifulSoup(f,"html.parser")

table = soup.find('table')

import pandas as pd
data = pd.read_html(str(table),flavor='bs4')[0]

In above code datafile is your downloaded html page. Alternatively you can use requests Python module to get the webpage and store it inside the variable.

The second block imports BeautifulSoup and I am loading that html page into soup variable. Again this block can be done using requests if you are going to scrape live website.

Table variable stores the first table tag which is the table we need to scrape.

Pandas is used to read the table variable and store in form Python table…

Excel Macro to Find and Replace in multiple sheet

Below are the two Sub-procedure which can be used to find and replace particular search term with replace value. So this macro will run on multiple sheet in same directory. In below code you have to make following changes according to your settings.

Pathname - I have mentioned the directory where all my sheet is present. This macro will run for all the sheet present in the directory you mention.

Filename  - If you notice I have give as "*csv". So I was using macro for CSV files in the particular directory. Change  the extension accordingly ex:xlsx or xls.

Search and Replacement - Use this to specify the search term and replace term.

Columns(3) - Here I am running this search and replace only for column C in the sheet.

Worksheets(1) - This means I am running the macro only in first sheet in the workbook.

How to run: To run this macro open a blank Excel Sheet and press 'ALT + F11'.
It will open Visual Basic editor. And right click on sheet -> Insert -> Module. Then…

Python Selenium click code

Using class name and JavaScript Method:

Using ID name and JavaScript Method:

Normal method:

Excel fill empty cell with above value

In some cases your sheet might have a column where the value is present only one time for a set of values. It happens when you export the report with group by option in SQL.

So we would like to have all our rows to have the corresponding value. Let's see how this can be done in Excel.

1. Select the column which you want to fill the empty cell with the value above. Only select the range which you want to fill. To select the range first click on the start cell and press F5. Then enter the last value, for example if the last value is in 500th row, then enter A500 and press SHIFT and OK.

2. Once the range of rows are selected, Click on Home -> Find & Select  ->  Go To Special. In Go To Special dialog box will appear, then check Blanks option.

3. Once you click OK the blank cells will be selected. On the blank cell enter the formula for above cell. For example: if value is in A3, enter A3 in the blank cell and press CTRL + ENTER.

Costliest phone from Samsung that you can buy in India

Every year Samsung showcase their new flagship phone. This year we have bezel less flagship phone Galaxy S8. Now it is available for sale from major retail and e-tail.

Galaxy S8 cost you ₹57,900, however the costliest phone from Samsung is it's Galaxy Note 7 with the price tag of ₹62,900. Galaxy Note 7 shipping has been stopped due to the reported battery problem. This leaves us with Galaxy S8 as their costliest phone for now.

Other S series from Samsung Galaxy costed about 30k to 40k range. Galaxy Note 8 is expected to release this year which will costlier than S8.
Features of Galaxy S8: 8MP Front-Facing Camera Take clearer, sharper, more detailed selfies with Samsung’s best smartphone camera yet.
Fingerprint Scanner
Easily unlock your device using a new fingerprint scanner on the back of the device.
Water & Dust Resistance With an IP68 water resistant rating, the Samsung Galaxy S8 can resist a splash or accidental dunk.
Bixby Bixby Vision - Intelligent Interface with natural…