Numpy Arrays ﺯﺍ ﻢﯿﻘﺘﺴﻣ ﺭﻮﻃ ﻪﺑ ﺎﻫ ﻩﺩﺍﺩ ﻢﺴﺠﺗ
.ﺖﺳﺎﻤﺷ ﯼﺍﺮﺑ ﺵﺯﻮﻣﺁ ﻦﯾﺍ ﺲﭘ ؟ﺪﯿﺘﺴﻫ ﻥﻮﺘﯾﺎﭘ ﺭﺩ ﺎﻫ ﻩﺩﺍﺩ ﺪﻣﺁﺭﺎﮐ ﻢﺴﺠﺗ ﯼﺍﺮﺑ ﯼﺍ ﻪﯾﺎﭘ ﻥﺩﺭ
.ﮒﺭﺰﺑ ﯼﺎﻫ ﻩﺩﺍﺩ ﻪﻋﻮﻤﺠﻣ ﺪﻣﺁﺭﺎﮐ ﺖﯾﺮﯾﺪﻣ ﯼﺍﺮﺑ ﻥﻮﺘﯾﺎﭘ ﺞﯾﺍﺭ ﻩﺩﺍﺩ ﺭﺎﺘﺧﺎﺳ ﮏﯾ ،ﺪﻫﺩ ﯽﻣ ﺶﺷ
.ﺖﺳﺍ ﺐﺳﺎﻨﻣ ﺎﻤﺷ ﯼﺍﺮﺑ ﺵﺯﻮﻣﺁ ﻦﯾﺍ ، ﺪﯿﺘﺴﻫ ﻥﻮﺘﯾﺎﭘ ﺭﺩ ﺎﻫ ﻩﺩﺍﺩ ﻢﺴﺠﺗ ﻊﯾﺮﺳ ﺱﺎﺳﺍ ﻭ ﻪﯾﺎﭘ
ﯽﺷﺯﻮﻣﺁ ﯼﺎﻫ ﻪﻧﻮﻤﻧ
. matplotlib ﻭ NumPy :ﺪﯿﻨﮐ ﺩﺭﺍﻭ ﺩﻮﺧ ﻥﻮﺘﯾﺎﭘ ﻪ
import numpy as np
import matplotlib.pyplot as plt
.ﻢﯿﻧﺰﺑ ﻪﺟﺮﯿﺷ ﻢﯾﺍ ﻩﺩﺮﮐ ﻩﺩﺎﻣﺁ ﺎﻤﺷ ﯼﺍﺮﺑ ﻪﮐ ﯽﻌﻗﺍﻭ ﯼﺎﯿﻧﺩ ﯼﺎﻫ ﻩﺩﺍﺩ ﯼﺎﻫ ﻪﻧﻮﻤﻧ ﻪﺑ ﻥﻮﻨﮐ
ﻥﺎﻣﺯ ﺖﺷﺬﮔ ﺎﺑ ﻡﺎﻬﺳ ﺖﻤﯿﻗ :1D ﯼﺎﻫ ﻩﺩﺍﺩ ﻢﺴﺠﺗ
.ﺪﻨﮐ ﯽﻣ ﻢﺴﺠﺗ ﻩﺩﺎﺳ ﻂﺧ ﺭﺍﺩﻮﻤﻧ ﮏﯾ ﺯﺍ ﻩﺩﺎﻔﺘﺳﺍ ﺎﺑ (ﺯﻭﺭ 30) ﻩﺎﻣ ﮏﯾ ﻝﻮﻃ ﺭﺩ ﺍﺭ ﻡﺎﻬﺳ ﻪﻧ
days = np.arange(1, len(stock_prices) + 1)
# Array of daily stock prices (30 elements)
stock_prices = [102.5, 105.2, 103.8, 101.9, 104.7, 106.3, 107.1, 105.5,
108.2, 109.0, 107.8, 106.5, 108.9, 109.5, 110.2, 109.8,
111.5, 112.3, 110.9, 113.1, 111.8, 114.2, 113.5, 115.0,
114.7, 116.2, 115.8, 117.5, 116.9, 118.1]
# Plot the array in a line plot
plt.plot(days, stock_prices)
plt.xlabel('Day')
plt.ylabel('Price ($)')
plt.title('Stock Prices Over Time')
plt.show()
.ﺖﺳﺍ ﻝﺁ ﻩﺪﯾﺍ numpy ﻪﯾﺍﺭﺁ ﮏﯾ ﺭﺩ ﺩﻮﺟﻮﻣ ﯽﻧﺎﻣﺯ ﯼﺮﺳ ﯼﺎﻫ ﻩﺩﺍﺩ ﻢﺴﺠﺗ ﯼﺍﺮﺑ ﻩ
:ﯽﺟﻭﺮﺧ
:ﺮﯾﺯ ﺡﺮﺷ ﻪﺑ ، ﺪﯿﻨﮐ ﺪﯿﻟﻮﺗ ﯽﻓﺩﺎﺼﺗ ﺭﻮﻃ ﻪﺑ ﺍﺭ ﺩﻮﺧ ﻡﺎﻬﺳ ﺖﻤﯿﻗ 1D ﻪﯾﺍﺭﺁ ﺪﯿﻧﺍﻮﺗ ﯽﻣ ، ﺶ
days = np.arange(1, 31)
stock_prices = np.random.normal(100, 5, size=days.shape)
ﻥﺯﻭ ﻞﺑﺎﻘﻣ ﺭﺩ ﺪﻗ :1D ﻩﺩﺍﺩ ﻪﯾﺍﺭﺁ ﻭﺩ ﻢﺴﺠﺗ
.ﺖﺳﺍ ﻞﺣ ﻩﺍﺭ ﯽﮔﺪﻨﮐﺍﺮﭘ ﺡﺮﻃ ،- ﺎﻫ ﯽﮕﺘﺴﺒﻤﻫ ﻞﯿﻠﺤﺗ ﻭ ﻪﯾﺰﺠﺗ ﯼﺍﺮﺑ ،ﻝﺎﺜﻣ ﻥﺍﻮﻨﻋ ﻪﺑ - ﻢﯿﻨ
.ﺪﻨﮐ ﯽﻣ ﻩﺩﺎﻔﺘﺳﺍ ﻪﯾﺍﺭﺁ ﻭﺩ ﺮﻫ ﯼﻭﺭ ﺮﺑ ﯽﮔﺪﻨﮐﺍﺮﭘ ﺭﺍﺩﻮﻤﻧ ﺩﺎﺠﯾﺍ ﯼﺍﺮﺑscatter
height = np.random.normal(170, 10, 100) # Random heights generated using a normal distribution with mean 170 and stdev 10
weight = np.random.normal(70, 8, 100) # Random heights generated using a normal distribution with mean 70 and stdev 8
plt.scatter(height, weight)
plt.xlabel('Height (cm)')
plt.ylabel('Weight (kg)')
plt.title('Height vs. Weight')
plt.show()
:ﯽﺟﻭﺮﺧ
ﺎﻫ ﻥﺎﮑﻣ ﺮﺳﺍﺮﺳ ﺭﺩ ﺎﻣﺩ :ﯼﺪﻌﺑ ﻭﺩ ﻪﯾﺍﺭﺁ ﮏﯾ ﻢﺴﺠﺗ
.ﺪﻧﻮﺷ ﯽﻣ ﺪﯿﻟﻮﺗ ﺩﺍﺮﮕﯿﺘﻧﺎﺳ ﻪﺟﺭﺩ 30 ﻭ ﺩﺍﺮﮕﯿﺘﻧﺎﺳ ﻪﺟﺭﺩ 15 ﻦﯿﺑ ﺮﯾﺩﺎﻘﻣ ﺎﺑ ﺖﺧﺍﻮﻨﮑﯾ ﻊﯾﺯ
# 2D data grid: 10x10 temperature recordings over a rectangular area
temperatures = np.random.uniform(low=15, high=30, size=(10, 10)) # Temperature in °C
plt.imshow(temperatures, cmap='hot', interpolation='nearest')
plt.colorbar(label='Temperature (°C)')
plt.title('Temperature Heatmap')
plt.show()
.ﺖﺳﺍ ﺕﻭﺎﻔﺘﻣ ﺮﯾﻮﺼﺗ ﺡﻮﺿﻭ ﻭ .ﺖﺳﺍ ﻡﺯﻻ ﻩﺩﺍﺩ ﯼﺪﻨﺑ ﻪﻧﺍﺩ ﺕﺭﻮﺻ ﺭﺩ ، ﯽﺑﺎﯾ ﻥﻭﺭﺩ ﺵﻭﺭ ﮏﯾ ﻭ
:ﯽﺟﻭﺮﺧ
ﯽﻟﺎﻣ ﯽﻧﺎﻣﺯ ﯼﺮﺳ :ﻪﻧﺎﮔﺪﻨﭼ ﯼﺪﻌﺑ 1 ﯼﺎﻫ ﻪﯾﺍﺭﺁ ﻢﺴﺠﺗ
.ﺩﺭﺍﺪﻧ ﯽﻧﺍﺪﻨﭼ ﺕﻭﺎﻔﺗ ﻢﯾﺩﺍﺩ ﻡﺎﺠﻧﺍ ﻼًﺒﻗ ﻪﭽﻧﺁ ﺎﺑ ﺪﻧﻭﺭ ﻦﯾﺍ ، ﺪﺷﺎﺑ ﺩﻮﺟﻮﻣ ﯼﻭﺎﺴﻣ ﻩﺯﺍﺪﻧﺍ
days = np.arange(1, 31)
stock_A = np.random.normal(100, 5, size=days.shape)
stock_B = np.random.normal(120, 10, size=days.shape)
stock_C = np.random.normal(90, 8, size=days.shape)
plt.plot(days, stock_A, label='Stock A')
plt.plot(days, stock_B, label='Stock B')
plt.plot(days, stock_C, label='Stock C')
plt.xlabel('Day')
plt.ylabel('Price ($)')
plt.title('Stock Prices Over Time')
plt.legend()
plt.show()
.ﺩﻮﺷ ﯽﻣ ﻪﻓﺎﺿﺍ ﻞﺻﺎﺣ ﻢﺴﺠﺗ ﻪﺑ ﻪﮐ ﺖﺳﺍ "ﺕﺎﻋﻮﻨﺼﻣ" ﺪﻨﻧﺎﻣ ﯽﻠﺒﻗ ﯼﺎﻫ ﻞﻤﻌﻟﺍﺭﻮﺘﺳﺩ ﺭﺩ ﺰﯿﭼ ﻪ
:ﯽﺟﻭﺮﺧ
ﻥﺪﯿﭽﯿﭘ
.ﺩﺮﮐ ﻢﺴﺠﺗ ﺎﻣﺮﮔ ﯼﺎﻫ ﭗﻣ ﺪﻨﻧﺎﻣ ﺮﺗ ﻩﺪﯿﭽﯿﭘ ﯼﺎﻫﺩﺮﮑﯾﻭﺭ ﺎﺗ ﻪﺘﻓﺮﮔ ﻂﺧ ﺡﺮﻃ ﺪﻨﻧﺎﻣ ﺮﺗ ﻩﺩﺎﺳ