Pandas: Extract date from a given column of a given DataFrame
Pandas: String and Regular Expression Exercise-36 with Solution
Write a Pandas program to extract date (format: mm-dd-yyyy) from a given column of a given DataFrame.
Sample Solution:
Python Code :
import pandas as pd
import re as re
df = pd.DataFrame({
'company_code': ['Abcd','EFGF', 'zefsalf', 'sdfslew', 'zekfsdf'],
'date_of_sale': ['12/05/2002','16/02/1999','05/09/1998','12/02/2022','15/09/1997'],
'sale_amount': [12348.5, 233331.2, 22.5, 2566552.0, 23.0]
})
print("Original DataFrame:")
print(df)
def find_valid_dates(dt):
#format: mm-dd-yyyy
result = re.findall(r'\b(1[0-2]|0[1-9])/(3[01]|[12][0-9]|0[1-9])/([0-9]{4})\b',dt)
return result
df['valid_dates']=df['date_of_sale'].apply(lambda dt : find_valid_dates(dt))
print("\nValid dates (format: mm-dd-yyyy):")
print(df)
Sample Output:
Original DataFrame: company_code date_of_sale sale_amount 0 Abcd 12/05/2002 12348.5 1 EFGF 16/02/1999 233331.2 2 zefsalf 05/09/1998 22.5 3 sdfslew 12/02/2022 2566552.0 4 zekfsdf 15/09/1997 23.0 Valid dates (format: mm-dd-yyyy): company_code date_of_sale sale_amount valid_dates 0 Abcd 12/05/2002 12348.5 [(12, 05, 2002)] 1 EFGF 16/02/1999 233331.2 [] 2 zefsalf 05/09/1998 22.5 [(05, 09, 1998)] 3 sdfslew 12/02/2022 2566552.0 [(12, 02, 2022)] 4 zekfsdf 15/09/1997 23.0 []
Python Code Editor:
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Previous: Write a Pandas program to check whether two given words present in a specified column of a given DataFrame.
Next: Write a Pandas program to extract only words from a given column of a given DataFrame.
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Python: Tips of the Day
Python: Cache results with decorators
There is a great way to cache functions with decorators in Python. Caching will help save time and precious resources when there is an expensive function at hand.
Implementation is easy, just import lru_cache from functools library and decorate your function using @lru_cache.
from functools import lru_cache @lru_cache(maxsize=None) def fibo(a): if a <= 1: return a else: return fibo(a-1) + fibo(a-2) for i in range(20): print(fibo(i), end="|") print("\n\n", fibo.cache_info())
Output:
0|1|1|2|3|5|8|13|21|34|55|89|144|233|377|610|987|1597|2584|4181| CacheInfo(hits=36, misses=20, maxsize=None, currsize=20)
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