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| − | [[  | + | [[IS428_AY2019-20T1_Assign_Li_Xiaohang| <font color="#FFFFFF">Challenge Overview</font>]]  | 
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'''Text data:''' <br>  | '''Text data:''' <br>  | ||
| − | Report data: The dataset contains individual reports of shaking/damage by neighborhood over time, from 6th April to 11th April.  | + | Report data: The dataset contains individual reports of shaking/damage by neighborhood over time, from 6th April to 11th April. <br>  | 
| + | During the data exploration stage, it is observed that there are missing values for damage level. 0 is filled in for the missing values during calculation.  | ||
=Pre-Analysis Data Processing=  | =Pre-Analysis Data Processing=  | ||
Latest revision as of 21:34, 13 October 2019
Mini-Challenge 1: Crowdsourcing for Situational Awareness
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Introducation of the Data
The dataset countains two parts, image data and text data: 
Image data: 
 
- Pre-quake Shake Map
 - Major-quake Shake Map
 - St. Himark City Map by Location
 
Text data: 
Report data: The dataset contains individual reports of shaking/damage by neighborhood over time, from 6th April to 11th April. 
During the data exploration stage, it is observed that there are missing values for damage level. 0 is filled in for the missing values during calculation.
Pre-Analysis Data Processing
1. The timestamp given in the dataset is in 'YYYY-MM-DD hh:mm:ss' format. For easy aggregation, a new column 'Date' is created. 
2. The 'Location' column is identified as a measure when imported to Tableau. It is configured to a dimension for visualization purposes later.