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NEW QUESTION: 1
Refer to the exhibit.

The MGCP debugs were captured on a Cisco IOS MGCP PRI gateway registered to a Cisco Unified CM.
Assume that this gateway had no active calls and will not take any new calls for the next 3 minutes. What time it will send the next NTFY message to the Cisco Unified CM?
A. Jan 10 05:55:40.130
B. Jan 10 05:56:05.130
C. Jan 10 05:56:35.130
D. Jan 10 05:55:45.130
E. Jan 10 05:55:50.130
Answer: E
Explanation:
Explanation/Reference:
Explanation:
NTFY keepalive messages are sent every 15 seconds, even when no calls are active.

NEW QUESTION: 2
Which three statements are true for IBM Commerce Software: Starter Stores?
A. Starter Stores do not offer support for unstructured content such as how-to videos and user manuals
B. Starter Stores are quick and easy to implement, and eliminate or minimize reliance on IT support
C. Starter Stores are available for B2C web store implementation only
D. Starter Stores are available for both B2B and B2C web store implementations
E. Start Stores include pre-built widgets to help quickly and build store pages
Answer: B,D,E

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


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