Learn how to generate statistics and correlations to understand data.
- [Narrator] One of the key EDA functions performed on any…data set is to understand the data…through descriptive statistics.…Descriptive statistics provide characteristics…of each data element.…We do the same for the campaign's data set.…Pandas has an easy way to do descriptive statistics…through the function describe.…We do that for this data frame.…As you can see, for each column in the data set,…count, mean, standard deviation, and quartiles…are printed as part of the command.…
For example, the price column has a mean of 40.08…and a standard deviation of 8.22.…The range varies from 30 to 50 with 40 being the median.…Another key function then for understanding data…is correlation analysis between the target variable…and the feature variables.…In this data set, the target variable is conversion.…We want to understand how conversion is impacted…by other feature variables like price, discount,…gender, age, etc.…
We do this through the corr function for the data frame.…A value closer to 1 or -1 will indicate…significant correlation.…
- Setting up Cloud DataLlb for exploratory data analytics
- Segmentation and profiling
- Reading and writing data from BigQuery
- Managing cloud storage buckets
- Creating visualizations of BigQuery data with the GCP Charting API
- Managing Datalab instances
Skill Level Intermediate
Predictive Customer Analyticswith Kumaran Ponnambalam1h 37m Intermediate
1. Exploration Options in GCP
2. Cloud Datalab Basics
3. Datalab: BigQuery
4. Datalab: Cloud Storage
5. Datalab: Visualizations
6. EDA with GCP: Use Case
7. Managing Datalab
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