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Pandas: Replace more than one value with other values in a given DataFrame

Pandas: String and Regular Expression Exercise-22 with Solution

Write a Pandas program to replace more than one value with other values in a given DataFrame.

Sample Solution:

Python Code :

import pandas as pd
df = pd.DataFrame({
    'company_code': ['A','B', 'C', 'D', 'A'],
    '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("\nReplace A with c:")
df = df.replace(["A", "D"], ["X", "Y"])
print(df)

Sample Output:

Original DataFrame:
  company_code date_of_sale  sale_amount
0            A   12/05/2002      12348.5
1            B   16/02/1999     233331.2
2            C   25/09/1998         22.5
3            D   12/02/2022    2566552.0
4            A   15/09/1997         23.0

Replace A with c:
  company_code date_of_sale  sale_amount
0            X   12/05/2002      12348.5
1            B   16/02/1999     233331.2
2            C   25/09/1998         22.5
3            Y   12/02/2022    2566552.0
4            X   15/09/1997         23.0

Python Code Editor:


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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)