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NEW QUESTION: 1
Which of the following standards or encryption types is the MOST secure for wireless networking?
A. AES
B. WEP
C. DES
D. TKIP
Answer: A

NEW QUESTION: 2
HOTSPOT
You have a Hyper-V host named Hyperv1 that runs Windows Server 2012 R2. Hyperv1 hosts a virtual machine named Server1. Server1 uses a disk named Server1.vhdx that is stored locally on Hyperv1.
You stop Server1, and then you move Server1.vhdx to an iSCSI target that is located on another server.
You need to configure Server1 to meet the following requirements:
- Ensure that Server1 can start by using Server1.vhdx.
- Prevent Server1.vhdx from consuming more than 500 IOPS on the iSCSI target.
Which two objects should you configure? To answer, select the appropriate two objects in the answer area.

Answer:
Explanation:

NEW QUESTION: 3
次の形式のsalesDataという名前のPythonデータフレームがあります。

データフレームは、次のように長いデータ形式にピボット解除する必要があります。

変換を実行するには、Pythonのpandas.melt（）関数を使用する必要があります。
コードセグメントをどのように完成させる必要がありますか？ 回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。

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