Answer:
Explanation:
To convert larger units to smaller units (i.e. take a number of gigabytes and convert it down in to megabytes, kilobytes, or bytes) you simply multiply the original number by 1,024 for each unit size along the way to the final desired unit
The RAM of G.Skill Trident Z Neo 3600 will be highly recommended for online and video lecturing.
<h3>What is RAM?</h3>
This is referred to random access memory and store information which can be retrieved quickly.
The RAM of G.Skill Trident Z Neo 3600 is 32GB which ensures the speed of the processor is fast.
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The answer is b It allows you to modify the animation for any properties using F-Curves. The Graph editor has two modes, F-Curve for Actions, and Drivers for Drivers. Both are very similar in function.
The limpel-ziv (lz77) compression technique is used by the GNU zip (gzip) tool to produce a compression ratio of 60–70%.
<h3>How do methods for data compression function? Describe the LZW algorithm.</h3>
Compression methods lower the amount of memory needed to hold pictures and the number of bytes needed to represent data. Compression improves the amount of data that can be delivered over the internet and enables the storage of more photos on a given media.
Abraham Lempel, Jacob Ziv, and Terry Welch developed the table-based lookup technique known as LZW compression to compress a file into a smaller file. The TIFF image format and the GIF image format are two frequently used file formats that employ LZW compression.
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Answer:
import pandas as pd #importing pandas library as pd
import matplotlib.pyplot as plt #importing matplotlib.pyplot as plt
pop=pd.read_csv('nycHistPop.csv') #reading the csv file
borough=input('Enter borough name:') #asking the user for borough namme
# image=input('Enter image name:')
# pop['Fraction']=pop[borough]/pop['Total']
# pop.plot(x='Year', y='Fraction')
print("Minimum population",pop[borough].min()) #printing the minimum population of borough
print("Maximum population",pop[borough].max()) #printing the maximum population of borough
print("Average population",pop[borough].mean()) #printing the average population of borough
print("Standard deviation",pop[borough].std()) #printing the standard deviation of borough
# fig=plt.gcf()
# fig.savefig(image)
Explanation: