Numpy Savetxt is a method to save an array to a text file or CSV file. In this coding tutorial, I will show you the implementation of the NumPy savetxt() method using the best examples I have compiled.

First of all, let’s import all the necessary libraries required for this tutorial. Here I am using only NumPy library.

`import numpy as np`

## How to Save One Dimensional Numpy array using numpy.savetxt()

In this section, I will create a one-dimensional NumPy array. Then after saving it to both as a text file and CSV file.

`array_1d = np.array([10,30,40,20])`

**Saving to text file**

`np.savetxt("array_1d.txt",array_1d,delimiter=",")`

Here I am passing the filename, the array I want to save and delimiter to split the array elements after the comma.

**Output**

**Saving to a CSV File**

You can save it to a CSV file by just changing the name of the file.

`np.savetxt("array_1d.csv",[array_1d],delimiter=",",fmt="%d")`

There is something you should be careful about. You have to pass your 1D Numpy array inside the square bracket. And * fmt=”%d”* as by default the array will be stored as float type. Here We are using the values of integer type.

**Output**

You can also add a header and footer argument inside the * np.savetxt()* method. Just execute the following code.

`np.savetxt("array_1d_with_hf.csv",[array_1d],delimiter=",",fmt="%d",header="This is header",footer="This is footer")`

**Output**

## Save Two Dimensional Numpy array using numpy.savetxt()

The above example was for one dimensional array. Now let’s save the two-dimensional array as a text and CSV file. Let’s create a Two Dimensional Array.

`array_2d = np.array([[10,30,20],[60,50,40],[5,6,7]])`

**Saving to a text file**

`np.savetxt("array_2d.txt",array_2d,delimiter=",")`

**Output**

**Saving to a CSV File**

`np.savetxt("array_2d.csv",array_2d,delimiter=",",fmt="%d")`

**Output**

You can also see how I am not the square bracket for array_2d as here it is not required.

## How to Save a Structured Numpy array in CSV file?

You can also save a Structured Numpy array to a CSV file. Those Numpy arrays that has a custom data type (dtype) is a structured Numpy array. Below is the code for the Structured Numpy array.

```
#type of the numpy array structure
dtype = [('Name', (np.str_, 10)), ('RollNo', np.int32), ('Marks', np.float64)]
strud_array = np.array([("Sahil",15,92),("Abhishek",16,98),("John",17,100)],dtype=dtype)
```

Here I am defining the name, roll no, and marks with their corresponding type.

Now you can save the strud_array with the header as Name, RollNo, and Marks. It will act as the column name in your CSV File.

`np.savetxt('strud_array.csv', strud_array, delimiter=',', fmt=['%s' , '%d', '%f'], header='Name,RollNo,Marks', comments='')`

**Output**

## Save more than one NumPy array

In this section, I will show you how you can save more than one Numpy array to both text file and CSV file.

Let’s create three Numpy array.

```
array1 = np.arange(100,200,10)
array2 = np.arange(200,300,10)
array3 = np.arange(300,400,10)
```

**Save to text file**

`np.savetxt("3_array.txt",(array1,array2,array3))`

**Output**

**Saving to CSV File**

`np.savetxt("3_array.csv",(array1,array2,array3),delimiter=",",fmt="%d")`

**Output**

Here In both cases, I am passing the set of Numpy array. All arrays will be appended to the next row of the file.

## Conclusion

Numpy savetxt method is very useful for saving and retrieving your own dataset. You can manipulate or change any existing dataset and save it. These are examples I have coded for getting a deep understanding. If you have any queries then you can contact us for more information.

Source:

Official Numpy Savetxt Documentation

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