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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)