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小墨
2023-10-05 03:40:12 +08:00
parent cb4f82d60a
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61
leetcode-cn/originData/[no content]calculate-orders-within-each-interval.json Normal file
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{
"data": {
"question": {
"questionId": "3160",
"questionFrontendId": "2893",
"categoryTitle": "Database",
"boundTopicId": 2468419,
"title": "Calculate Orders Within Each Interval",
"titleSlug": "calculate-orders-within-each-interval",
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"sampleTestCase": "{\"headers\": {\"Orders\": [\"minute\", \"order_count\"]}, \"rows\": {\"Orders\":[[1,0],[2,2],[3,4],[4,6],[5,1],[6,4],[7,1],[8,2],[9,4],[10,1],[11,4],[12,6]]}}",
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"insert into Orders (minute, order_count) values ('3', '4')",
"insert into Orders (minute, order_count) values ('4', '6')",
"insert into Orders (minute, order_count) values ('5', '1')",
"insert into Orders (minute, order_count) values ('6', '4')",
"insert into Orders (minute, order_count) values ('7', '1')",
"insert into Orders (minute, order_count) values ('8', '2')",
"insert into Orders (minute, order_count) values ('9', '4')",
"insert into Orders (minute, order_count) values ('10', '1')",
"insert into Orders (minute, order_count) values ('11', '4')",
"insert into Orders (minute, order_count) values ('12', '6')"
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82
leetcode-cn/originData/[no content]the-wording-game.json Normal file
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leetcode-cn/originData/change-data-type.json Normal file
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{
"data": {
"question": {
"questionId": "3069",
"questionFrontendId": "2886",
"categoryTitle": "Algorithms",
"boundTopicId": 2467490,
"title": "Change Data Type",
"titleSlug": "change-data-type",
"content": "<pre>\nDataFrame <code>students</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n| grade | float |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to correct the errors:</p>\n\n<p>The <code>grade</code> column is stored as floats,&nbsp;convert it to integers.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:\n</strong>DataFrame students:\n+------------+------+-----+-------+\n| student_id | name | age | grade |\n+------------+------+-----+-------+\n| 1 | Ava | 6 | 73.0 |\n| 2 | Kate | 15 | 87.0 |\n+------------+------+-----+-------+\n<strong>Output:\n</strong>+------------+------+-----+-------+\n| student_id | name | age | grade |\n+------------+------+-----+-------+\n| 1 | Ava | 6 | 73 |\n| 2 | Kate | 15 | 87 |\n+------------+------+-----+-------+\n<strong>Explanation:</strong> \nThe data types of the column grade is converted to int.</pre>\n",
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leetcode-cn/originData/count-visited-nodes-in-a-directed-graph.json Normal file
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leetcode-cn/originData/create-a-dataframe-from-list.json Normal file
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{
"data": {
"question": {
"questionId": "3062",
"questionFrontendId": "2877",
"categoryTitle": "Algorithms",
"boundTopicId": 2467481,
"title": "Create a DataFrame from List",
"titleSlug": "create-a-dataframe-from-list",
"content": "<p>Write a solution to <strong>create</strong> a DataFrame from a 2D list called <code>student_data</code>. This 2D list contains the IDs and ages of some students.</p>\n\n<p>The DataFrame should have two columns, <code>student_id</code> and <code>age</code>, and be in the same order as the original 2D list.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>student_data:<strong>\n</strong><code>[\n [1, 15],\n [2, 11],\n [3, 11],\n [4, 20]\n]</code>\n<strong>Output:</strong>\n+------------+-----+\n| student_id | age |\n+------------+-----+\n| 1 | 15 |\n| 2 | 11 |\n| 3 | 11 |\n| 4 | 20 |\n+------------+-----+\n<strong>Explanation:</strong>\nA DataFrame was created on top of student_data, with two columns named <code>student_id</code> and <code>age</code>.\n</pre>\n",
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55
leetcode-cn/originData/create-a-new-column.json Normal file
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{
"data": {
"question": {
"questionId": "3066",
"questionFrontendId": "100007",
"categoryTitle": "Algorithms",
"boundTopicId": 2394353,
"title": "Create a New Column",
"titleSlug": "create-a-new-column",
"content": "<pre>\nDataFrame <code>employees</code>\n+-------------+--------+\n| Column Name | Type. |\n+-------------+--------+\n| name | object |\n| salary | int. |\n+-------------+--------+\n</pre>\n\n<p>A&nbsp;company plans to provide its employees with a bonus.</p>\n\n<p>Write a solution to create a new column name <code>bonus</code> that contains the <strong>doubled values</strong> of the <code>salary</code> column.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong>\nDataFrame employees\n+---------+--------+\n| name | salary |\n+---------+--------+\n| Piper | 4548 |\n| Grace | 28150 |\n| Georgia | 1103 |\n| Willow | 6593 |\n| Finn | 74576 |\n| Thomas | 24433 |\n+---------+--------+\n<strong>Output:</strong>\n+---------+--------+--------+\n| name | salary | bonus |\n+---------+--------+--------+\n| Piper | 4548 | 9096 |\n| Grace | 28150 | 56300 |\n| Georgia | 1103 | 2206 |\n| Willow | 593 | 13186 |\n| Finn | 74576 | 149152 |\n| Thomas | 24433 | 48866 |\n+---------+--------+--------+\n<strong>Explanation:</strong> \nA new column bonus is created by doubling the value in the column salary.</pre>\n",
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leetcode-cn/originData/display-the-first-three-rows.json Normal file
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{
"data": {
"question": {
"questionId": "3065",
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"categoryTitle": "Algorithms",
"boundTopicId": 2467489,
"title": "Display the First Three Rows",
"titleSlug": "display-the-first-three-rows",
"content": "<pre>\nDataFrame: <code>employees</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| employee_id | int |\n| name | object |\n| department | object |\n| salary | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to display the <strong>first <code>3</code> </strong>rows<strong> </strong>of this DataFrame.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>DataFrame employees\n+-------------+-----------+-----------------------+--------+\n| employee_id | name | department | salary |\n+-------------+-----------+-----------------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n| 60 | Annabelle | InformationTechnology | 37678 |\n| 49 | Jonathan | HumanResources | 23793 |\n| 43 | Khaled | Administration | 40454 |\n+-------------+-----------+-----------------------+--------+\n<strong>Output:</strong>\n+-------------+---------+-------------+--------+\n| employee_id | name | department | salary |\n+-------------+---------+-------------+--------+\n| 3 | Bob | Operations | 48675 |\n| 90 | Alice | Sales | 11096 |\n| 9 | Tatiana | Engineering | 33805 |\n+-------------+---------+-------------+--------+\n<strong>Explanation:</strong> \nOnly the first 3 rows are displayed.</pre>\n",
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55
leetcode-cn/originData/drop-duplicate-rows.json Normal file
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"categoryTitle": "Algorithms",
"boundTopicId": 2467488,
"title": "Drop Duplicate Rows",
"titleSlug": "drop-duplicate-rows",
"content": "<pre>\nDataFrame customers\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| customer_id | int |\n| name | object |\n| email | object |\n+-------------+--------+\n</pre>\n\n<p>There are some duplicate rows in the DataFrame based on the <code>email</code> column.</p>\n\n<p>Write a solution to remove these duplicate rows and keep only the <strong>first</strong> occurrence.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:</strong>\n+-------------+---------+---------------------+\n| customer_id | name | email |\n+-------------+---------+---------------------+\n| 1 | Ella | emily@example.com |\n| 2 | David | michael@example.com |\n| 3 | Zachary | sarah@example.com |\n| 4 | Alice | john@example.com |\n| 5 | Finn | john@example.com |\n| 6 | Violet | alice@example.com |\n+-------------+---------+---------------------+\n<strong>Output: </strong> \n+-------------+---------+---------------------+\n| customer_id | name | email |\n+-------------+---------+---------------------+\n| 1 | Ella | emily@example.com |\n| 2 | David | michael@example.com |\n| 3 | Zachary | sarah@example.com |\n| 4 | Alice | john@example.com |\n| 6 | Violet | alice@example.com |\n+-------------+---------+---------------------+\n<strong>Explanation:</strong>\nAlic (customer_id = 4) and Finn (customer_id = 5) both use john@example.com, so only the first occurrence of this email is retained.\n</pre>\n",
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leetcode-cn/originData/drop-missing-data.json Normal file
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55
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55
leetcode-cn/originData/get-the-size-of-a-dataframe.json Normal file
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leetcode-cn/originData/method-chaining.json Normal file
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"content": "<pre>\nDataFrame <code>animals</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| name | object |\n| species | object |\n| age | int |\n| weight | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to list the names of animals that weigh <strong>strictly more than</strong> <code>100</code> kilograms.</p>\n\n<p>Return the&nbsp;animals sorted by weight in <strong>descending order</strong>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong>Example 1:</strong></p>\n\n<pre>\n<strong>Input:</strong> \nDataFrame animals:\n+----------+---------+-----+--------+\n| name | species | age | weight |\n+----------+---------+-----+--------+\n| Tatiana | Snake | 98 | 464 |\n| Khaled | Giraffe | 50 | 41 |\n| Alex | Leopard | 6 | 328 |\n| Jonathan | Monkey | 45 | 463 |\n| Stefan | Bear | 100 | 50 |\n| Tommy | Panda | 26 | 349 |\n+----------+---------+-----+--------+\n<strong>Output:</strong> \n+----------+\n| name |\n+----------+\n| Tatiana |\n| Jonathan |\n| Tommy |\n| Alex |\n+----------+\n<strong>Explanation:</strong> \nAll animals weighing more than 100 should be included in the results table.\nTatiana&#39;s weight is 464, Jonathan&#39;s weight is 463, Tommy&#39;s weight is 349, and Alex&#39;s weight is 328.\nThe results should be sorted in descending order of weight.</pre>\n\n<p>&nbsp;</p>\n<p>In Pandas, <strong>method chaining</strong> enables us to&nbsp;perform operations on a DataFrame without breaking up each operation into a separate line or creating multiple temporary variables.&nbsp;</p>\n\n<p>Can you complete this&nbsp;task in just <strong>one line </strong>of code using method chaining?</p>\n",
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leetcode-cn/originData/modify-columns.json Normal file
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leetcode-cn/originData/rename-columns.json Normal file
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"content": "<pre>\nDataFrame <code>students</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| id | int |\n| first | object |\n| last | object |\n| age | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to rename the columns as follows:</p>\n\n<ul>\n\t<li><code>id</code> to <code>student_id</code></li>\n\t<li><code>first</code> to <code>first_name</code></li>\n\t<li><code>last</code> to <code>last_name</code></li>\n\t<li><code>age</code> to <code>age_in_years</code></li>\n</ul>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:\n</strong>+----+---------+----------+-----+\n| id | first | last | age |\n+----+---------+----------+-----+\n| 1 | Mason | King | 6 |\n| 2 | Ava | Wright | 7 |\n| 3 | Taylor | Hall | 16 |\n| 4 | Georgia | Thompson | 18 |\n| 5 | Thomas | Moore | 10 |\n+----+---------+----------+-----+\n<strong>Output:</strong>\n+------------+------------+-----------+--------------+\n| student_id | first_name | last_name | age_in_years |\n+------------+------------+-----------+--------------+\n| 1 | Mason | King | 6 |\n| 2 | Ava | Wright | 7 |\n| 3 | Taylor | Hall | 16 |\n| 4 | Georgia | Thompson | 18 |\n| 5 | Thomas | Moore | 10 |\n+------------+------------+-----------+--------------+\n<strong>Explanation:</strong> \nThe column names are changed accordingly.</pre>\n",
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55
leetcode-cn/originData/reshape-data-concatenate.json Normal file
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"title": "Reshape Data: Concatenate",
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"content": "<pre>\nDataFrame <code>df1</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\nDataFrame <code>df2</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\n</pre>\n\n<p>Write a solution to concatenate these two DataFrames <strong>vertically</strong> into one DataFrame.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\ndf1</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n+------------+---------+-----+\n<strong>df2\n</strong>+------------+------+-----+\n| student_id | name | age |\n+------------+------+-----+\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+------+-----+\n<strong>Output:</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 1 | Mason | 8 |\n| 2 | Ava | 6 |\n| 3 | Taylor | 15 |\n| 4 | Georgia | 17 |\n| 5 | Leo | 7 |\n| 6 | Alex | 7 |\n+------------+---------+-----+\n<strong>Explanation:\n</strong>The two DataFramess are stacked vertically, and their rows are combined.</pre>\n",
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55
leetcode-cn/originData/reshape-data-melt.json Normal file
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"title": "Reshape Data: Melt",
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"content": "<pre>\nDataFrame <code>report</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| product | object |\n| quarter_1 | int |\n| quarter_2 | int |\n| quarter_3 | int |\n| quarter_4 | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to <strong>reshape</strong> the data so that each row represents sales data for a product in a specific quarter.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<p><strong class=\"example\">Example 1:</strong></p>\n\n<pre>\n<strong>Input:\n</strong>+-------------+-----------+-----------+-----------+-----------+\n| product | quarter_1 | quarter_2 | quarter_3 | quarter_4 |\n+-------------+-----------+-----------+-----------+-----------+\n| Umbrella | 417 | 224 | 379 | 611 |\n| SleepingBag | 800 | 936 | 93 | 875 |\n+-------------+-----------+-----------+-----------+-----------+\n<strong>Output:</strong>\n+-------------+-----------+-------+\n| product | quarter | sales |\n+-------------+-----------+-------+\n| Umbrella | quarter_1 | 417 |\n| SleepingBag | quarter_1 | 800 |\n| Umbrella | quarter_2 | 224 |\n| SleepingBag | quarter_2 | 936 |\n| Umbrella | quarter_3 | 379 |\n| SleepingBag | quarter_3 | 93 |\n| Umbrella | quarter_4 | 611 |\n| SleepingBag | quarter_4 | 875 |\n+-------------+-----------+-------+\n<strong>Explanation:</strong>\nThe DataFrame is reshaped from wide to long format. Each row represents the sales of a product in a quarter.\n</pre>\n",
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55
leetcode-cn/originData/reshape-data-pivot.json Normal file
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"title": "Reshape Data: Pivot",
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"content": "<pre>\nDataFrame <code>weather</code>\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| city | object |\n| month | object |\n| temperature | int |\n+-------------+--------+\n</pre>\n\n<p>Write a solution to <strong>pivot</strong> the data so that each row represents temperatures for a specific month, and each city is a separate column.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong class=\"example\">Example 1:</strong>\n<strong>Input:</strong>\n+--------------+----------+-------------+\n| city | month | temperature |\n+--------------+----------+-------------+\n| Jacksonville | January | 13 |\n| Jacksonville | February | 23 |\n| Jacksonville | March | 38 |\n| Jacksonville | April | 5 |\n| Jacksonville | May | 34 |\n| ElPaso | January | 20 |\n| ElPaso | February | 6 |\n| ElPaso | March | 26 |\n| ElPaso | April | 2 |\n| ElPaso | May | 43 |\n+--------------+----------+-------------+\n<strong>Output:</strong><code>\n+----------+--------+--------------+\n| month | ElPaso | Jacksonville |\n+----------+--------+--------------+\n| April | 2 | 5 |\n| February | 6 | 23 |\n| January | 20 | 13 |\n| March | 26 | 38 |\n| May | 43 | 34 |\n+----------+--------+--------------+</code>\n<strong>Explanation:\n</strong>The table is pivoted, each column represents a city, and each row represents a specific month.</pre>\n",
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55
leetcode-cn/originData/select-data.json Normal file
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"content": "<pre>\nDataFrame students\n+-------------+--------+\n| Column Name | Type |\n+-------------+--------+\n| student_id | int |\n| name | object |\n| age | int |\n+-------------+--------+\n\n</pre>\n\n<p>Write a solution to select the name and age of the student with <code>student_id = 101</code>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p>&nbsp;</p>\n<pre>\n<strong>Example 1:\nInput:</strong>\n+------------+---------+-----+\n| student_id | name | age |\n+------------+---------+-----+\n| 101 | Ulysses | 13 |\n| 53 | William | 10 |\n| 128 | Henry | 6 |\n| 3 | Henry | 11 |\n+------------+---------+-----+\n<strong>Output:</strong>\n+---------+-----+\n| name | age | \n+---------+-----+\n| Ulysses | 13 |\n+---------+-----+\n<strong>Explanation:\n</strong>Student Ulysses has student_id = 101, we select the name and age.</pre>\n",
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184
leetcode-cn/originData/split-array-into-maximum-number-of-subarrays.json Normal file
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