diff --git a/yo006yo/gitUpdate.bat b/yo006yo/gitUpdate.bat
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+git status .
+
+@pause
+
+git add .
+git commit -m"update yo006yo,"
+start git push
\ No newline at end of file
diff --git a/yo006yo/meta.md b/yo006yo/meta.md
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+---
+tags: [HKDI, pending, kaggle]
+---
+
+# yo006yo
+
+### Collect Open / Real-Time Data, Visualization and Analysis
diff --git a/yo006yo/task1/ProjectBrief_EA_DigitalData_v1d.pdf b/yo006yo/task1/ProjectBrief_EA_DigitalData_v1d.pdf
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diff --git a/yo006yo/task1/package.json b/yo006yo/task1/package.json
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+{
+  "name": "yo006yo",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1",
+    "gitUpdate": "git add . && git commit -m'update,'&& git push"
+  },
+  "keywords": [],
+  "author": "",
+  "license": "ISC"
+}
diff --git a/yo006yo/task1/quotation.md b/yo006yo/task1/quotation.md
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+---
+tags: [pending, kaggle]
+---
+
+# task1
+
+## Brief
+
+### You are required to collect open data and real-time data.
+
+### Part 1: Jupyter notebook Data Analysis and suggestion of actionable items
+
+- Download the Top 200 common passwords by country 2021 database from www.kaggle.com
+- Manipulate and rearrange the data if necessary
+- Visualize the data using 8 or more charts using Python programming in Jupyter notebook.
+- The sunburst chart, heat map, and pair-plot must be used.
+- 1 or more 3D chart is essential.
+- 1 or more map, such as choropleth map in plotly should be displayed.
+- Analyze the charts (and data) which may reveal some facts to us.
+- Provide insights and suggest actionable items.
+- (You may add other related data set(s) to enrich your insights and suggestions.)
+
+### Part 2: Real-time data processing and visualization, in Jupyter notebook.
+
+- Collect and store real-time data using the API of HK Accident and Emergency waiting time (of Hospitals) in NoSQL database (e.g., MongoDB).
+  - remarks : https://data.gov.hk/en-data/dataset/hospital-hadata-ae-waiting-time/resource/164c3478-1791-4f9e-94d9-70d2374a48e2
+- The data collection duration should be 3 or more days, within November and/or December.
+- The collection frequency should be every 15 minutes or less.
+- Create Jupyter Notebook to read data into a Pandas dataframe.
+- (You may export the data, using Mongo Compass, to a json file first.)
+- Process and visualize the data.
+- Produce 3 or more charts.
+- You are encouraged to use python 3D visualization techniques too.
+- Analyze the charts (and data) to reveal some facts.
+- Provide insights / comments / suggestions.
+
+### Items should include:
+
+- Exported collection(s) of the open data / samples of real-time data, from MongoDB
+- Jupyter Notebooks that visualize and analyze the data sets, with summary, conclusions and so on in Markdown.
+- Demonstrate data collection process and present all results / insights, in a video.
+- Upload everything to Moodle 1 week after the last lesson.