How do I successfully create ordered categorical data from an existing column?

By -

Here's a dataframe - 'dist_copy' - with values I would like to change to categorical. I've only included one column, but there are additional columns I want to convert as well.

state dist_id pct_free_reduced_lunch
Illinois 1111 80% - 100%
Illinois 1112 0 - 20%
Illinois 2365 40% - 60%

dist_copy.pct_free_reduced_lunch.unique()

returns

array(['80% - 100%', '60% - 80%', '0 - 20%', '20% - 40%', '40% - 60%'], dtype=object)

Previously, I used pd.Categorical to change all the values in the 'pct_free_reduced_lunch' column to 'categorical', and established the order, with this code:

dist_copy['pct_free_reduced_lunch'] = pd.Categorical(dist_copy['pct_free_reduced_lunch'], 
     categories=['0 — 20%','20% — 40%', '40% — 60%', '60% — 80%',  '80% - 100%'], ordered=True)

Today, this code isn't working, and only retains the first value, changing all other values to NaN.

state dist_id pct_free_reduced_lunch
Illinois 1111 80% - 100%
Illinois 1112 NaN
Illinois 2365 NaN

What am I doing wrong, or misunderstanding?

UPDATE: The above code began to work AFTER I copy-pasted each categorical value from the array returned by unique() into the categories array inside the pd.Categorical function, in the desired order.

When I merely entered them from scratch, NaNs were created.

WHY? I would really love to know!



from Recent Questions - Stack Overflow https://ift.tt/3pNl1la
https://ift.tt/eA8V8J

Comments

Post a Comment

Popular posts from this blog

Today Walkin 14th-Sept

By -
Image
14th Sept 2017 ( GO Through all List) Read Walkin details properly , Try to call company before attending if possible !!! ==================================== 1. Myntra through fresherworld (Call Based , Venue shared to shortlisted candidates) _____________________________ 2. Magna : Hiring for Client Harman : C++
Read more

Hibernate Search - Elasticsearch with JSON manipulation

By -
Elasticsearch with JSON manipulation Elasticsearch ships with many features. It is possible that at some point, one feature you need will not be exposed by the Search DSL. To work around such limitations, Hibernate Search provides ways to: Transform the HTTP request sent to Elasticsearch for search queries. Read the raw JSON of the HTTP response received from Elasticsearch for search queries. Direct changes to the HTTP request may conflict with Hibernate Search features and be supported differently by different versions of Elasticsearch. Similarly, the content of the HTTP response may change depending on the version of Elasticsearch, depending on which Hibernate Search features are used, and even depending on how Hibernate Search features are implemented. Thus, features relying on direct access to HTTP requests or responses cannot be guaranteed to continue to work when upgrading Hibernate Search, even for micro upgrades (x.y.z to x.y.(z+1)). Use this at your own risk.
Read more

Spring Elasticsearch Operations

By -
Elasticsearch Operations Spring Data Elasticsearch uses two interfaces to define the operations that can be called against an Elasticsearch index. These are ElasticsearchOperations and ReactiveElasticsearchOperations. Whereas the first is used with the classic synchronous implementations, the second one uses reactive infrastructure. The default implementations of the interfaces offer: Read/Write mapping support for domain types. A rich query and criteria api. Resource management and Exception translation. ElasticsearchTemplate The ElasticsearchTemplate is an implementation of the ElasticsearchOperations interface using the Transport Client. @Configuration public class TransportClientConfig extends ElasticsearchConfigurationSupport {   @Bean   public Client elasticsearchClient() throws UnknownHostException {                      Settings settings = Settings.builder().put("cluster.name", "elasticsearch").build();     TransportClient client = new P
Read more