Explanation
A pie chart is the best choice to show the composition between the categories of the survey response data set.
A pie chart represents the whole with a circle, divided by slices into parts. Each slice shows the relative size of each category as a percentage of the total. A pie chart is useful when the categories are mutually exclusive and add up to 100%. The table shows the favorite color and the number of responses for each color, which can be easily converted into percentages. A pie chart can show how each color contributes to the total number of responses.
Option A is incorrect because a histogram is used to show how data points are distributed along a numerical scale. The survey response data set is not numerical, but categorical.
Option C is incorrect because a line chart is used to show trends or changes over time. The survey response data set does not have a time dimension.
Option D is incorrect because a scatter plot is used to show the relationship between two numerical variables.
The survey response data set does not have two numerical variables.
Option E is incorrect because a waterfall chart is used to show how an initial value is increased or decreased by a series of intermediate values. The survey response data set does not have an initial value or intermediate values.
References:
How to Choose the Right Chart for Your Data - Infogram
How to Choose the Right Data Visualization | Tutorial by Chartio
Find the Best Visualizations for Your Metrics - The Data School
How to choose the best chart or graph for your data

INNER JOIN は、両方のテーブルで結合条件に一致する行のみを返します。LEFT JOIN は、左側のテーブルのすべての行と右側のテーブルから一致する行を返します。一致する行がない場合は NULL を返します。この場合、顧客テーブルは左側のテーブルで、店内取引テーブルは右側のテーブルです。結合条件は、両方のテーブルに共通する customer_id 列に基づいています。
INNER JOIN を実行するには、次の SQL クエリを使用できます。
SELECT * FROM customer INNER JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; このクエリは、以下に示すように 9 行のデータを返します。
顧客 ID | 名前 | 姓 | 性別 | 配偶者の有無 | 取引 ID | 金額 | 日付 1 | MARC | TESCO | M | Y | 1 | 1000 | 2020-01-01 1 | MARC | TESCO | M | Y | 2 | 5000 | 2020-01-02 2 | ANNA | MARTIN | F | N | 3 | 2000 | 2020-01-03 2 | ANNA | MARTIN | F | N | 4 | 3000 | 2020-01-04 3 | EMMA | JOHNSON | F | Y | 5 | 4000 | 2020-01-05 4 | DARIO | PENTAL | M | N | 6 | 5000 | 2020-01-06 5 | ELENA | SIMSON| F| N|7|6000|2020-01-07 6|TIM|ROBITH|M|N|8|7000|2020-01-08 7|MILA|MORRIS|F|N|9|8000|2020-01-09 LEFT JOIN を実行するには、次の SQL クエリを使用できます。
SELECT * FROM customer LEFT JOIN in_store_transactions ON customer.customer_id = in_store_transactions.customer_id; このクエリは、以下に示すように 15 行のデータを返します。
顧客ID|名前|姓|性別|婚姻状況|取引ID|金額|日付 1|MARC|TESCO|M|Y|1|1000|2020-01-01 1|MARC|TESCO|M|Y|2|5000|2020-01-02 2|ANNA|MARTIN|F|N|3|2000|2020-01-03 2|ANNA|MARTIN|F|N|4|3000|2020-01-04 3|EMMA|JOHNSON|F|Y|5|4000|2020-01-05 4|DARIO|PENTAL|M|N|6|5000|2020-01-06 5|ELENA|SIMSON||F||N||7||6000||2020-01-07 6||TIM||ROBITH||M||N||8||7000||2020-01-08 7||MILA||MORRIS||F||N||9||8000||2020-01-09 8||JENNY||DWARTH||F||Y||NULL||NULL||NULL ご覧のとおり、取引のない顧客 (customer_id = 8) も結果に含まれていますが、transaction_id、amount、およびdate列の値は NULL になっています。
したがって、正解は C: 内側: 9 行、左: 15 行です。