chore(i18n,chn): manually downloaded curriculum (#42858)
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---
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id: 5e46f7e5ac417301a38fb929
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title: Demographic Data Analyzer
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title: 人口统计数据分析器
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challengeType: 10
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forumTopicId: 462367
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dashedName: demographic-data-analyzer
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---
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# --description--
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In this challenge you must analyze demographic data using Pandas. You are given a dataset of demographic data that was extracted from the 1994 Census database.
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在这个挑战中，你必须使用 Pandas 对人口统计进行分析。 你将获得从 1994 年人口普查数据库中提取的人口统计数据数据集。
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You can access [the full project description and starter code on Repl.it](https://repl.it/github/freeCodeCamp/boilerplate-demographic-data-analyzer).
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你可以[在 Replit 上查看整个项目的具体描述和初始代码](https://replit.com/github/freeCodeCamp/boilerplate-demographic-data-analyzer)。
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After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
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点击此链接，fork 这个项目。 一旦你根据 “README.md” 中的说明完成项目，请提交你的项目链接到下面。
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We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
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我们仍在开发 Python 数据分析课程的交互式教学。 现在，你需要使用其他资源来学习如何通过这一挑战。
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# --hints--
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It should pass all Python tests.
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它应该通过所有的 Python 测试。
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```js
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---
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id: 5e46f7f8ac417301a38fb92a
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title: Medical Data Visualizer
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title: 医疗数据可视化工具
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challengeType: 10
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forumTopicId: 462368
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dashedName: medical-data-visualizer
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---
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# --description--
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In this project, you will visualize and make calculations from medical examination data using matplotlib, seaborn, and pandas.
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在这个项目中，你将要使用 matplotlib，seaborn 和 pandas 来对健康检查数据进行数据可视化和计算。
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You can access [the full project description and starter code on Repl.it](https://repl.it/github/freeCodeCamp/boilerplate-medical-data-visualizer).
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你可以[在 Replit 上查看整个项目的具体描述和初始代码](https://replit.com/github/freeCodeCamp/boilerplate-medical-data-visualizer)。
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After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
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打开此链接后，fork 这个项目。 一旦你根据 “README.md” 中的说明完成项目，请提交你的项目到下面的链接。
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We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
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我们仍在开发 Python 数据分析课程的交互式课程部分。 现在，你需要使用其他资源来学习如何通过这一挑战。
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# --hints--
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It should pass all Python tests.
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它应该通过所有的 Python 测试。
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```js
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---
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id: 5e46f802ac417301a38fb92b
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title: Page View Time Series Visualizer
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title: 页面访问量的时间序列可视化工具
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challengeType: 10
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forumTopicId: 462369
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dashedName: page-view-time-series-visualizer
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---
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# --description--
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For this project you will visualize time series data using a line chart, bar chart, and box plots. You will use Pandas, matplotlib, and seaborn to visualize a dataset containing the number of page views each day on the freeCodeCamp.org forum from 2016-05-09 to 2019-12-03. The data visualizations will help you understand the patterns in visits and identify yearly and monthly growth.
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对于这个项目，你将使用线图、条形图和箱形图对时间序列数据进行可视化。 你将要使用 Pandas、matplotlib 和 seaborn 来对数据集进行可视化，这个数据集包含从 2016-05-09 到 2019-12-03 每一天在 freeCodeCamp.org 论坛的页面访问量。 这个数据可视化将帮助你了解访问的模式，并且显示年增长和月增长情况。
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You can access [the full project description and starter code on Repl.it](https://repl.it/github/freeCodeCamp/boilerplate-page-view-time-series-visualizer).
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你可以 [在 Replit 上查看整个项目的具体描述和初始代码](https://replit.com/github/freeCodeCamp/boilerplate-page-view-time-series-visualizer)。
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After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
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点击此链接，fork 这个项目。 一旦你根据 “README.md” 中的说明完成项目，请提交你的项目到下面的链接。
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We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
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我们仍在开发 Python 数据分析课程的交互式课程部分。 现在，你将需要使用其他资源来学习如何通过这一挑战。
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# --hints--
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It should pass all Python tests.
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它应该通过所有的 Python 测试。
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```js
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---
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id: 5e4f5c4b570f7e3a4949899f
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title: Sea Level Predictor
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title: 海平面预报器
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challengeType: 10
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forumTopicId: 462370
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dashedName: sea-level-predictor
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---
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# --description--
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In this project, you will analyze a dataset of the global average sea level change since 1880. You will use the data to predict the sea level change through year 2050.
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在本项目中，您将分析自 1880 年以来全球平均海平面变化的数据集。 您将使用这些数据来预测到 2050 年的海平面变化。
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You can access [the full project description and starter code on Repl.it](https://repl.it/github/freeCodeCamp/boilerplate-sea-level-predictor).
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你可以在 [Replit 上查看整个项目的具体描述和初始代码](https://replit.com/github/freeCodeCamp/boilerplate-sea-level-predictor)。
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After going to that link, fork the project. Once you complete the project based on the instructions in 'README.md', submit your project link below.
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打开此链接后，fork 这个项目。 一旦你根据 “README.md” 中的说明完成项目，请提交你的项目到下面的链接。
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We are still developing the interactive instructional part of the data analysis with Python curriculum. For now, you will have to use other resources to learn how to pass this challenge.
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我们仍在开发 Python 数据分析课程的交互式课程部分。 现在，你需要使用其他资源来学习如何通过这一挑战。
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# --hints--
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It should pass all Python tests.
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它应该通过所有的 Python 测试。
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```js
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