DataFrame.tensor

danfo.DataFrame.tensor
Note: Tensorflow tensors have single dtype, and will replace any string value with NaN. Use with care.
Examples
Node
Browser
const dfd = require("danfojs-node")
​
let data = { "A": [-20, 30, 47.3, -20] ,
             "B": [34, -4, 5, 6] ,
             "C": [20, 20, 30, 30]}
             
let df = new dfd.DataFrame(data)
let tf_tensor = df.tensor
​
console.log(tf_tensor.dtype);
​
console.log(tf_tensor);
​
tf_tensor.print()
​
Output
float32
​
Tensor {
  kept: false,
  isDisposedInternal: false,
  shape: [ 4, 3 ],
  dtype: 'float32',
  size: 12,
  strides: [ 3 ],
  dataId: {},
  id: 0,
  rankType: '2'
}
​
Tensor
    [[-20       , 34, 20],
     [30        , -4, 20],
     [47.2999992, 5 , 30],
     [-20       , 6 , 30]]
String values in a Tensor are represented as NaN, so ensure to transform them before working with tensor representations.
Node
Browser
const dfd = require("danfojs-node")
​
let data = { "Abs": [20.2, 30, 47.3] ,
             "Count": [34, 5, 6] ,
             "country code": ["NG", "FR", "GH"] }
​
​
let df = new dfd.DataFrame(data)
let tf_tensor = df.tensor
​
console.log(tf_tensor.dtype);
​
console.log(tf_tensor);
​
tf_tensor.print()
​
Output
float32 
​
Tensor {
  kept: false,
  isDisposedInternal: false,
  shape: [ 3, 3 ],
  dtype: 'float32',
  size: 9,
  strides: [ 3 ],
  dataId: {},
  id: 0,
  rankType: '2'
}
​
Tensor
    [[20.2000008, 34, NaN],
     [30        , 4 , NaN],
     [47.2999992, 5 , NaN]]

DataFrame.nUnique

DataFrame.print

Last modified 8mo ago

Copy link