np.savetxt() and np.loadtxt() for text in NumPy - Step-by-Step Execution

Concept Flow - np.savetxt() and np.loadtxt() for text

Create or have a numpy array

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Use np.savetxt() to write array to text file

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File saved on disk as plain text

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Use np.loadtxt() to read text file back into numpy array

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Array loaded in memory, same shape and values

This flow shows saving a numpy array to a text file and then loading it back as an array.

Execution Sample

NumPy

import numpy as np
arr = np.array([[1, 2], [3, 4]])
np.savetxt('data.txt', arr, fmt='%d')
loaded = np.loadtxt('data.txt', dtype=int)

Save a 2x2 integer array to 'data.txt' and load it back into 'loaded'.

Execution Table

Step	Action	Input/Condition	Result/Output
1	Create array	arr = [[1, 2], [3, 4]]	arr is a 2x2 numpy array with integers
2	Call np.savetxt	filename='data.txt', arr, fmt='%d'	File 'data.txt' created with text: 1 2 3 4
3	Call np.loadtxt	filename='data.txt', dtype=int	loaded is a 2x2 numpy array with values [[1, 2], [3, 4]]
4	Check equality	np.array_equal(arr, loaded)	True

💡 Finished saving and loading array, data matches original

Variable Tracker

Variable	Start	After Step 1	After Step 3	Final
arr	undefined	[[1 2] [3 4]]	[[1 2] [3 4]]	[[1 2] [3 4]]
loaded	undefined	undefined	[[1 2] [3 4]]	[[1 2] [3 4]]

Key Moments - 3 Insights

Why do we need to specify fmt='%d' in np.savetxt?

Without fmt='%d', np.savetxt saves floats by default, which can add decimals. Specifying '%d' saves integers exactly as in the execution_table step 2.

What happens if the file 'data.txt' does not exist when calling np.loadtxt?

np.loadtxt will raise a FileNotFoundError because it cannot find the file to read, as shown in execution_table step 3 where the file must exist.

Does np.loadtxt always return the same shape array as saved?

Yes, if the file format matches and data is consistent, np.loadtxt returns the same shape, as seen in execution_table step 3 and variable_tracker.

Visual Quiz - 3 Questions

Look at the execution_table, what is the content of 'data.txt' after step 2?

A "1 2\n3 4"

B "[1 2]\n[3 4]"

C "1,2\n3,4"

D "1.0 2.0\n3.0 4.0"

💡 Hint

Check the Result/Output column in execution_table row 2 for the exact file content.

At which step does the variable 'loaded' get its value?

A Step 1

B Step 2

C Step 3

D Step 4

💡 Hint

Look at the Action column in execution_table where np.loadtxt is called.

If we remove fmt='%d' from np.savetxt, how would the file content change?

A It would save the array as binary

B It would save integers as floats with decimals

C It would not save anything

D It would save the array with commas

💡 Hint

Refer to key_moments question about fmt='%d' and execution_table step 2.

Concept Snapshot

np.savetxt(filename, array, fmt) saves a numpy array to a text file.
np.loadtxt(filename, dtype) loads the text file back as a numpy array.
Use fmt='%d' to save integers without decimals.
The saved file is plain text with rows and columns.
Loaded array matches the original shape and values.

Full Transcript

This lesson shows how to save a numpy array to a text file using np.savetxt and then load it back using np.loadtxt. First, we create a 2x2 integer array. Then, np.savetxt writes this array to a file named 'data.txt' with integer formatting to avoid decimals. Next, np.loadtxt reads the file and recreates the array in memory. The loaded array matches the original exactly in shape and values. Key points include specifying the format to control how data is saved and ensuring the file exists before loading. This process is useful for saving data in a human-readable text format and loading it later for analysis.