# finance\_pca

## ℹ️ Dataset info

Description: `PCA transformation of finance data. Principal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset`

Labels: `owner: upgini`  `dataset_type: public`  `dataset_source: markets`  

Search keys: `DATE`  

Row count: `6,630`

## ℹ️ Features info:

### f\_financial\_date\_finance\_pca\_0\_b9ec1c26

`Datatype`: `FLOAT` `Description`: `Finance data PCA component 0`

### f\_financial\_date\_finance\_pca\_1\_38f83e84

`Datatype`: `FLOAT` `Description`: `Finance data PCA component 1`

### f\_financial\_date\_finance\_pca\_2\_fe70a225

`Datatype`: `FLOAT` `Description`: `Finance data PCA component 2`

### f\_financial\_date\_finance\_pca\_3\_092fe927

`Datatype`: `FLOAT` `Description`: `Finance data PCA component 3`

### f\_financial\_date\_finance\_pca\_4\_ea45eea8

`Datatype`: `FLOAT` `Description`: `Finance data PCA component 4`

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