Comments (5)
it should. can you share your code and result?
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it should. can you share your code and result?
python:
from sklearn.preprocessing import StandardScaler
import pandas as pd
somedata = [[100,1000,2000, 3000] ,
[20, 30, 89, 12],
[1, 1, 1, 0]];
df = pd.DataFrame(data=somedata)
scaler = StandardScaler()
result = scaler.fit_transform(df)
Result is array([[ 1.39090235, 1.41375362, 1.41314026, 1.41420504],
[-0.47399466, -0.67564356, -0.65886309, -0.7028514 ],
[-0.91690769, -0.73811007, -0.75427717, -0.71135364]])
js:
const tf = require("@tensorflow/tfjs-node")
const dfd = require("danfojs-node")
let scaler = new dfd.StandardScaler()
let data = [
[100,1000,2000, 3000] ,
[20, 30, 89, 12],
[1, 1, 1, 0]
]
let df = new dfd.DataFrame(data)
scaler.fit(df)
let sf_enc = scaler.transform(df)
sf_enc.print()
Result is ═══╤═══════════════════╤═══════════════════╤═══════════════════╤═══════════════════╗
║ │ 0 │ 1 │ 2 │ 3 ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 0 │ -0.4258379936... │ 0.48414421081... │ 1.49523544311... │ 2.50632691383... ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 1 │ -0.5067253112... │ -0.4966143667... │ -0.4369599819... │ -0.5148140192... ║
╟───┼───────────────────┼───────────────────┼───────────────────┼───────────────────╢
║ 2 │ -0.5259360074... │ -0.5259360074... │ -0.5259360074... │ -0.5269471406... ║
from danfojs.
I will check it out
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@steveoni any updates on this?
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@ijakparov the standscalar bug is now fixed.
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