# cci\_pca

## ℹ️ Dataset info

Description: `PCA transformation of Consumer Confidence Index 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: economics` &#x20;

Search keys: `DATE` &#x20;

Row count: `8,563`

## ℹ️ Features info:

### f\_economic\_date\_cci\_pca\_0\_4b266261

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 0`

### f\_economic\_date\_cci\_pca\_1\_b2db99f5

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 1`

### f\_economic\_date\_cci\_pca\_2\_7441c668

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 2`

### f\_economic\_date\_cci\_pca\_3\_10646e17

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 3`

### f\_economic\_date\_cci\_pca\_4\_49e8923d

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 4`

### f\_economic\_date\_cci\_pca\_5\_b433b3c8

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 5`

### f\_economic\_date\_cci\_pca\_6\_aa7c1005

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 6`

### f\_economic\_date\_cci\_pca\_7\_17261951

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 7`

### f\_economic\_date\_cci\_pca\_8\_54959a61

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 8`

### f\_economic\_date\_cci\_pca\_9\_7f5e64a7

`Datatype`: `FLOAT` `Description`: `Consumer Confidence Index data PCA component 9`

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