Enriching Data
Updated
January 27, 2021
As part of building a recipe to analyse your data, you can enrich your data with information and functions built into Graphext. Enriching your data increases the information available which Graphext can use to build your recipe.
This can improve the accuracy of your predictions and refine your clusters as well as creating useful additional variables based on the existing content of your data.
Adding Data Enrichment
To extract additional information from your dataset using data enrichment, start building a recipe using the project setup wizard.
Some enrichment options require you to provide a unique API key.
How to Enrich Your Data?
- Start building a recipe using the project setup wizard.
- Pick a type of analysis.
- Choose an option from the sidebar to further indicate the type of analysis you want to conduct.
- Inside the recipe wizard belonging to the type of analysis you have chosen, open the 'Data Enrichment' form.
- Select the 'Enrich your data' dropdown.
- Choose an item or items from the dropdown.
- Complete the forms that appear below to configure your data enrichment.
- Done ... Your enrichment selections will be processed once you execute your project!
Data Enrichment Index
The data enrichment index provides details of the ways that you can enrich your data using information and functions built into Graphext.
Extract Date Components
Use a date variable to create new columns containing precise information about the month, week and day of a given date value.
Add Demographic Data for Spain Using Addresses
Requires Google Geocoding API key.
Use address variables to enrich your data with census information and coordinates from the Google Geocoding API. Addresses in your dataset will be associated with Spanish location-based demographic data such as age, marital status and education level.
Add Demographic Data for Spain Using Coordinates
Use latitude and longitude variables to enrich your data with census information. Geographies identifiable by coordinates in your dataset will be associated with Spanish location-based demographic data such as age, marital status and education level.
Extract Contact Info
Requires FullContact API key
Extract contact information from emails in your dataset using the FullContact API.
Infer Genders
Use the first names of people in your data to make predictions about their gender. This enrichment uses Graphext's own prediction algorithm.
Add Weather Information
Requires Dark Sky API Key
Use location and date information to obtain specific weather information using the Dark Sky API.
Analyze Text Sentiment - Google
Requires Google NLP API Key
Analyze the sentiment of text fields using the Google NLP API. This assigns positive or negative ratings to text in your data.
Analyze Text Sentiment - Meaningcloud
Requires Meaningcloud NLP API Key
Analyze the sentiment of text fields using the Meaningcloud NLP API. This assigns positive or negative ratings to text in your data.
Extract Text Topics
Requires Google NLP API Key
Identify the topic of text fields using the Google NLP API. This enrichment identifies the core theme of text values in your data.
Add Google Places Info
Requires Google Places API Key
Extract information about the most relevant places around a location using the Google Places API.
Categorize Text
Choose a set of words to assign tags for text values in your data.
Extract Entities from Text
Extract entities like names of people and organisations using a SpaCy model built into Graphext.
Extract Twitter Authors
Requires Twitter API Key
Use the Twitter API to obtain information about the author of a tweet.
Need Something Different?
We know that data isn't always clean and simple.
Have a look through these topics if you can't see what you are looking for.