Pandas: Check whether alphabetic values present in a given column of a DataFrame
Pandas: String and Regular Expression Exercise-10 with Solution
Write a Pandas program to check whether alphabetic values present in a given column of a DataFrame.
Note: isalpha() returns True if all characters in the string are alphabetic and there is at least one character, False otherwise.
Sample Solution:
Python Code :
import pandas as pd
df = pd.DataFrame({
'company_code': ['Company','Company a001','Company 123', 'abcd', 'Company 12'],
'date_of_sale ': ['12/05/2002','16/02/1999','25/09/1998','12/02/2022','15/09/1997'],
'sale_amount': [12348.5, 233331.2, 22.5, 2566552.0, 23.0]})
print("Original DataFrame:")
print(df)
print("\nWhether Alphabetic values present in company_code column?")
df['company_code_is_alpha'] = list(map(lambda x: x.isalpha(), df['company_code']))
print(df)
Sample Output:
Original DataFrame: company_code date_of_sale sale_amount 0 Company 12/05/2002 12348.5 1 Company a001 16/02/1999 233331.2 2 Company 123 25/09/1998 22.5 3 abcd 12/02/2022 2566552.0 4 Company 12 15/09/1997 23.0 Whether Alphabetic values present in company_code column? company_code ... company_code_is_alpha 0 Company ... True 1 Company a001 ... False 2 Company 123 ... False 3 abcd ... True 4 Company 12 ... False [5 rows x 4 columns]
Python Code Editor:
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Previous: Write a Pandas program to check whether alpha numeric values present in a given column of a DataFrame.
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Python: Time library
Time library provides lots of time related functions and methods and is good to know whether you're developing a website or apps and games or working with data science or trading financial markets. Time is essential in most development pursuits and Python's standard time library comes very handy for that.
Let's check out a few simple examples:
moment=time.strftime("%Y-%b-%d__%H_%M_%S",time.localtime())
import time time_now=time.strftime("%H:%M:%S",time.localtime()) print(time_now) date_now=time.strftime("%Y-%b-%d",time.localtime()) print(date_now)
Output:
11:36:34 2020-Nov-30
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