Take a glimpse into your data with polars

glimpse

I’ve said it before, and I’ll say it again: it’s important to know the data you’re working with before you start analyzing it. Below is a dataframe showing cereal brands.

shape: (77, 4)

mfr	type	calories	protein
str	str	i64	i64
"Nabisco"	"Cold"	70	4
"Quaker Oats"	"Cold"	120	3
"Kellogs"	"Cold"	70	4
"Kellogs"	"Cold"	50	4
"Ralston Purina"	"Cold"	110	2
…	…	…	…
"General Mills"	"Cold"	110	2
"General Mills"	"Cold"	110	1
"Ralston Purina"	"Cold"	100	3
"General Mills"	"Cold"	100	3
"General Mills"	"Cold"	110	2

Look into the dataset

Polars has a handy function, glimpse, that allows you to explore the dataset and see what values each column contains. More importantly, it displays one column per line, making it easier to view wider columns. Here’s how to use it:

df.glimpse(max_items_per_column=5)

Rows: 77
Columns: 4
$ mfr      <str> 'Nabisco', 'Quaker Oats', 'Kellogs', 'Kellogs', 'Ralston Purina'
$ type     <str> 'Cold', 'Cold', 'Cold', 'Cold', 'Cold'
$ calories <i64> 70, 120, 70, 50, 110
$ protein  <i64> 4, 3, 4, 4, 2

The max_items_per_column parameter controls how many values are shown for each column. The default is 10.

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