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NEW QUESTION: 1
Which two actions can be taken on Cisco LAN switches to provide basic denial-of-service protection?
(Choose two.)
A. Enable BPDU Guard
B. Enable IP Source Guard
C. Enable DHCP Snooping
D. Disable PortFast
E. Disable Spanning Tree Protocol
Answer: B,C

NEW QUESTION: 2
Scenario:
You are the senior network security administrator for your organization. Recently and junior engineer configured a site-to-site IPsec VPN connection between your headquarters Cisco ASA and a remote branch office.
You are now tasked with verifying the IKEvl IPsec installation to ensure it was properly configured according to designated parameters. Using the CLI on both the Cisco ASA and branch ISR, verify the IPsec configuration is properly configured between the two sites.
NOTE: the show running-config command cannot be used for this exercise.
Topology:



In what state is the IKE security association in on the Cisco ASA?
A. QM_IDLE
B. MM_ACTIVE
C. There are no security associations in place
D. ACTIVE(ACTIVE)
Answer: B
Explanation:
This can be seen from the "show crypto isa sa" command:


NEW QUESTION: 3
You have a Python data frame named salesData in the following format:
The data frame must be unpivoted to a long data format as follows:
You need to use the pandas.melt() function in Python to perform the transformation.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: dataFrame
Syntax: pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name='value', col_level=None)[source] Where frame is a DataFrame Box 2: shop Paramter id_vars id_vars : tuple, list, or ndarray, optional Column(s) to use as identifier variables.
Box 3: ['2017','2018']
value_vars : tuple, list, or ndarray, optional
Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.
Example:
df = pd.DataFrame({'A': {0: 'a', 1: 'b', 2: 'c'},
'B': {0: 1, 1: 3, 2: 5},
'C': {0: 2, 1: 4, 2: 6}})
pd.melt(df, id_vars=['A'], value_vars=['B', 'C'])
A variable value
0 a B 1
1 b B 3
2 c B 5
3 a C 2
4 b C 4
5 c C 6
References:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html

NEW QUESTION: 4
What is the maximum capacity of participants for a Cisco WebEx Meeting Center and Training Center meeting?
A. 0
B. 1
C. 2
D. 3
Answer: C
Explanation:
Section: (none)


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