Answer:
third partying and computer hackers.
Explanation:
Answer:An initial condition is an extra bit of information about a differential equation that tells you the value of the function at a particular point. Differential equations with initial conditions are commonly called initial value problems.
The video above uses the example
{
d
y
d
x
=
cos
(
x
)
y
(
0
)
=
−
1
to illustrate a simple initial value problem. Solving the differential equation without the initial condition gives you
y
=
sin
(
x
)
+
C
.
Once you get the general solution, you can use the initial value to find a particular solution which satisfies the problem. In this case, plugging in
0
for
x
and
−
1
for
y
gives us
−
1
=
C
, meaning that the particular solution must be
y
=
sin
(
x
)
−
1
.
So the general way to solve initial value problems is: - First, find the general solution while ignoring the initial condition. - Then, use the initial condition to plug in values and find a particular solution.
Two additional things to keep in mind: First, the initial value doesn't necessarily have to just be
y
-values. Higher-order equations might have an initial value for both
y
and
y
′
, for example.
Second, an initial value problem doesn't always have a unique solution. It's possible for an initial value problem to have multiple solutions, or even no solution at all.
Explanation:
Answer:
B. False
Explanation:
Numerous amount of games have narrative, there is an entire genres built around narratives. Any RPG game has a narrative and even bog standard FPS games have some sort of backstory and effects setting a mood.
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:
I believe they are icons.
