# np.mean() Function of NumPy Library in Python (3 Examples)

In this Python programming tutorial you’ll learn how to use the mean function of the NumPy library.

## Setting up the Examples

import numpy # Load numpy |

import numpy # Load numpy

x = np.array([[8, 2, 1, 7, 7, 5], # Constructing a NumPy array in Python [4, 10, 5, 9, 1, 4]]) print(x) # [[ 8 2 1 7 7 5] # [ 4 10 5 9 1 4]] |

x = np.array([[8, 2, 1, 7, 7, 5], # Constructing a NumPy array in Python [4, 10, 5, 9, 1, 4]]) print(x) # [[ 8 2 1 7 7 5] # [ 4 10 5 9 1 4]]

## Example 1: Calculate Mean of All Array Values in Python

print(np.mean(x)) # Computing the mean of all values # 5.25 |

print(np.mean(x)) # Computing the mean of all values # 5.25

## Example 2: Calculate Mean by Array Rows in Python

print(np.mean(x, axis = 1)) # Computing the mean by rows # [5. 5.5] |

print(np.mean(x, axis = 1)) # Computing the mean by rows # [5. 5.5]

## Example 3: Calculate Mean by Array Columns in Python

print(np.mean(x, axis = 0)) # Computing the mean by columns # [6. 6. 3. 8. 4. 4.5] |

print(np.mean(x, axis = 0)) # Computing the mean by columns # [6. 6. 3. 8. 4. 4.5]