Discussion on: Many Things You Can Do With Python Lists You May Have Missed

[Waylon Walker]

Great post, I had no idea there was a clear() method. You're missing out on one of my favorite features though! The * operator. I commonly use it along side list comprehensions.

For example take a pandas DataFrame and get all of the columns that include "price" in their name.

df_prices = df[col for col in df.columns if 'price' in col]

[John Au-Yeung]

Thanks for reading.

You mean make a filtered list with lost comprehension?

Or you mean using * to repeat items?

[Waylon Walker]

Lol, good catch. 😳 I think I took a break between the comment and finding a good example. Here is a real example of nearly the same thing if the DataFrame was a pyspark DataFrame. pyspark.select takes in column names as *args df.select('us_price', 'eu_price')

They can be selected programatically with a list comprehension and *unpacking.

df_prices = df.select(*[col for col in df.columns if 'price' in col])

[John Au-Yeung]

I see. The list comprehension is used as a predicate?

[Waylon Walker]

Not sure what you mean by predicate, the list comprehension is a filter.

price_cols = [col for col in df.columns if 'price' in col]
df_prices = df.select(*price_cols)

Here is a generally relatable example using the print statement

[ins] In [1]: fruits = ['apple', 'orange', 'orange', 'grape', 'pear']

[ins] In [2]: print(fruits)
['apple', 'orange', 'orange', 'grape', 'pear']

[ins] In [3]: print('apple', 'orange', 'orange', 'grape', 'pear')
apple orange orange grape pear

[ins] In [4]: print(*fruits)
apple orange orange grape pear

[ins] In [5]: print(*[fruit for fruit in fruits if 'p' in fruit])
apple grape pear

[John Au-Yeung]

That makes sense. I haven't seen this documented in many places. That's probably why I missed this.