## How can normalize the data in format (-3 ,-2,-1,0,1,2,3) if given data is in range (-1 to 1) using R or Python?

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Value: 0.344 -0.124 0.880 0 0.910 -0.800

You can try `cut()` function in R to divide values into intervals.

```value <- c(0.344, -0.124, 0.880, 0, 0.910, -0.800)
value.normalized <- cut(
x = value, breaks = seq(-1, 1, length.out = 8),
labels = -3:3, include.lowest = TRUE, right = TRUE
)

(value.normalized)
1  0  3  0  3  -3
Levels: -3 -2 -1 0 1 2 3
```

How do i normalize data from 0 to 1 range?, Read 22 answers by scientists with 37 recommendations from their colleagues to the I want to normalize my data for example in the range of 0 to 1. 1. About 2/ 3 of your cases will probably fall between 0.25 and 0.75. I am estimating a moderating model in Amos, and I ended up with r-squared values of 10 and 18. are�

You Can do something like this to normalize any data to given scale:

```>>> Data = [0.9, 0.2, 0.3, 0.4]
>>> lower, upper =-3, 3
>>> Data_norm = [lower + (upper - lower) * x for x in Data]
>>> Data_norm
[2.4000000000000004, -1.7999999999999998, -1.2000000000000002, -0.5999999999999996]
```

How to Normalize and Standardize Time Series Data in Python, How to normalize and standardize your time series data using scikit-learn in Python. 1. 2. 3. 4. 5. 6. "Date","Temperatures". "1981-01-01",20.7 Normalization is a rescaling of the data from the original range so that all values maximum values, that the resulting value will not be in the range of 0 and 1.

```In : from sklearn.preprocessing import minmax_scale

In : value = [0.344,-0.124,0.880,0,0.910,-0.800]

In : in_range = [-1, 1]

In : value_scaled = minmax_scale(value + in_range, feature_range=(-3,3))

In : value_scaled[:-2]

Out: array([ 1.032, -0.372,  2.64 ,  0.   ,  2.73 , -2.4  ])
```

Rescaling Data for Machine Learning in Python with Scikit-Learn, In this post you will discover two simple data transformation methods you can Your preprocessed data may contain attributes with a mixtures of to rescaling real valued numeric attributes into the range 0 and 1. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. # Normalize the data attributes for the c='r', label='centroid')

How to normalize data between -1 and 1?, With: x′=x−minxmaxx−minx. you normalize your feature x in [0,1]. To normalize in [−1,1] you can use: x″=2x−minxmaxx−minx−1. In general�

5 Data transformation, We'll illustrate the key ideas using data from the nycflights13 package, and use There are three other common types of variables that aren't used in this transformation for dealing with data that ranges across multiple orders of magnitude. 1 2013 1 1 0 #> 2 2013 1 2 3 #> 3 2013 1 3 4 #> 4 2013 1 4 3 #> 5 2013 1 5 3�

Normalize data - MATLAB normalize, N = normalize( A ) returns the vectorwise z-score of the data in A with center 0 and standard normalize operates along the first array dimension whose size does not equal 1. methodtype ) specifies the type of normalization for the given method . B = 3�3 8 1 6 3 5 7 4 9 2 Scale A so that its range is in the interval [ 0,1].