﻿ Pandas: Check whether alphabetic values present in a given column of a DataFrame - w3resource

# 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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## Python: Tips of the Day

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```