Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error **ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler** **in python**. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Table of Contents

## How ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler Error Occurs?

Today I get the following error **ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler** **in python**.

## How To Solve ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler Error ?

**How To Solve ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler Error ?**To Solve ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler Error I know that this post is old, but as I stumbled here, others will.. After running in the same problem and googling quite a bit I found a post

**ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler**To Solve ValueError: Found array with 0 sample (s) (shape= (0, 1) while a minimum of 1 is required by MinMaxScaler Error I know that this post is old, but as I stumbled here, others will.. After running in the same problem and googling quite a bit I found a post

## Solution 1

The `train_data`

variable has a length of 2264:

train_data = stock_value[:2264]

Then, when you go to fit the scaler, you go outside of `train_data`

‘s bounds on the third iteration of the for loop:

smoothing_window_size = 1100 for di in range(0, 4400, smoothing_window_size):

Notice the size of the data set in the tutorial. The training and testing chunks each have length 11,000, and the `smoothing_window_size`

is 2500, so it will never go exceed `train_data`

‘s boundaries.

## Solution 2

I know that this post is old, but as I stumbled here, others will.. After running in the same problem and googling quite a bit I found a post

so it seems that if you download a too small dataset it will throw that error. Download a .csv from 1962 and it’ll be big enough ;).

Now,I just have to find the right parameters for my dataset..as I’m adapting this to another type o prediction.. Hope it helps

**Summery**

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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