﻿ Pandas: Extract only punctuations from the specified column of a given DataFrame - w3resource

# Pandas: Extract only punctuations from the specified column of a given DataFrame

## Pandas: String and Regular Expression Exercise-31 with Solution

Write a Pandas program to extract only punctuations from the specified column of a given DataFrame.

Sample Solution:

Python Code :

``````import pandas as pd
import re as re
pd.set_option('display.max_columns', 10)
df = pd.DataFrame({
'company_code': ['c0001.','c000,2','c0003', 'c0003#', 'c0004,'],
'year': ['year 1800','year 1700','year 2300', 'year 1900', 'year 2200']
})
print("Original DataFrame:")
print(df)
def find_punctuations(text):
result = re.findall(r'[!"\\$%&\'()*+,\-.\/:;=#@?\[\\\]^_`{|}~]*', text)
string="".join(result)
return list(string)
df['nonalpha']=df['company_code'].apply(lambda x: find_punctuations(x))
print("\nExtracting punctuation:")
print(df)
``````

Sample Output:

```Original DataFrame:
company_code       year
0       c0001.  year 1800
1       c000,2  year 1700
2        c0003  year 2300
3       c0003#  year 1900
4       c0004,  year 2200

Extracting punctuation:
company_code       year nonalpha
0       c0001.  year 1800      [.]
1       c000,2  year 1700      [,]
2        c0003  year 2300       []
3       c0003#  year 1900      [#]
4       c0004,  year 2200      [,]
```

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```