Pandas: Extract word mention someone in tweets using @ from the specified column of a given DataFrame
Pandas: String and Regular Expression Exercise-26 with Solution
Write a Pandas program to extract word mention someone in tweets using @ 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({
'tweets': ['@Obama says goodbye','Retweets for @cash','A political endorsement in @Indonesia', '1 dog = many #retweets', 'Just a simple #egg']
})
print("Original DataFrame:")
print(df)
def find_at_word(text):
word=re.findall(r'(?<[email protected])\w+',text)
return " ".join(word)
df['at_word']=df['tweets'].apply(lambda x: find_at_word(x))
print("\Extracting @word from dataframe columns:")
print(df)
Sample Output:
Original DataFrame: tweets 0 @Obama says goodbye 1 Retweets for @cash 2 A political endorsement in @Indonesia 3 1 dog = many #retweets 4 Just a simple #egg \Extracting @word from dataframe columns: tweets at_word 0 @Obama says goodbye Obama 1 Retweets for @cash cash 2 A political endorsement in @Indonesia Indonesia 3 1 dog = many #retweets 4 Just a simple #egg
Python Code Editor:
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Next: Write a Pandas program to extract only number from the specified column of a given DataFrame.
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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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