# Pagination, not able to view all data queried from datastore

**URL:** <https://discourse.jupyter.org/t/pagination-not-able-to-view-all-data-queried-from-datastore/12467>\
**Category:** Notebook\
**Created:** [January 5, 2022, 9:40pm UTC](https://discourse.jupyter.org/t/pagination-not-able-to-view-all-data-queried-from-datastore/12467 "2022-01-05T21:40:03Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![tito](https://avatars.discourse-cdn.com/v4/letter/t/dfb087/32.png) [@tito](https://discourse.jupyter.org/u/tito)\
**Post date:** [January 5, 2022, 9:40pm UTC](https://discourse.jupyter.org/t/pagination-not-able-to-view-all-data-queried-from-datastore/12467/1 "2022-01-05T21:40:03Z")

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I am new to notebooks and can not get all of the data to display. When I pull the data from the original data source there are 50 rows. But when I execute from notebooks using the below, I only get 14. The data is large and I understand there is a limit, so using the max\_rows is not an option. I read you need pagination which can be accomplished with the below, but still not working. Any know please?

hash\_value = ‘myDataIdentifier’

while ‘LastEvaluatedKey’ in response:  
response = table.query(  
IndexName=‘table\_key-insertTS-index’,  
KeyConditionExpression = Key(‘table\_key’).eq(hash\_value)  
,ExclusiveStartKey=response[‘LastEvaluatedKey’]  
)  
data = response[‘Items’]

len(temp\_df.index)  
temp\_df = pd.DataFrame(data)  
temp\_df

---

<div class="post-metadata">

**Author:** ![bollwyvl](https://yyz1.discourse-cdn.com/flex031/user_avatar/discourse.jupyter.org/bollwyvl/32/904_2.png) [@bollwyvl](https://discourse.jupyter.org/u/bollwyvl)\
**Post date:** [January 5, 2022, 10:55pm UTC](https://discourse.jupyter.org/t/pagination-not-able-to-view-all-data-queried-from-datastore/12467/2 "2022-01-05T22:55:31Z")

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TL;DR: if you _really_ don’t care about maybe wedging your browser:

```auto
pandas.options.display.max_rows = pandas.options.display.max_columns = pandas.options.display.max_colwidth = int(1e6)

```

The pandas docs are _excellent_, once you know where to look. This particular thing is handled in [options](https://pandas.pydata.org/pandas-docs/stable/user_guide/options.html#overview), and an example right at the top of the page has what you need.