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NEW QUESTION: 1
A. Option D
B. Option B
C. Option A
D. Option C
Answer: B
Explanation:
https://www.microsoft.com/en-us/dynamics/crm-customer-center/set-up-customer-agreements-field-service.aspx#BKMK_CreateAgreement
NEW QUESTION: 2
What can you secure on the SAP BusinessObjects BI platform? (Choose two)
A. Applications
B. Queries
C. InfoProviders
D. Folders
Answer: A,D
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