It will most likely begin to crash and eventually just freeze , i'm guessing
Answer:
C. The specific field of study
C. change in anesthetic agent
Explanation:
In the consideration for the procedure, some information are required and examples are the strategy of the search/the database name. However, the area of study is not one of the information.
The animal use proposal can general be altered based on the type of change required. However, an anesthetic agent alteration is not a significant change.
Answer: my test says line graph soooo….
Explanation: if its what the test says
Answer:
In computing, extract, transform, load (ETL) is the general procedure of copying data from one or more sources into a destination system which represents the data differently from the source(s) or in a different context than the source(s).
Data extraction involves extracting data from homogeneous or heterogeneous sources; data transformation processes data by data cleansing and transforming them into a proper storage format/structure for the purposes of querying and analysis; finally, data loading describes the insertion of data into the final target database such as an operational data store, a data mart, data lake or a data warehouse. Hope this helps! PLEASE GIVEE ME BRAINLIST!!! =)
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:
