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TVisa Team1: Upload scrum reports & Deliverable 1 #36

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234 changes: 234 additions & 0 deletions t_visa_trends_team1/Deliverable 1/result.csv

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365 changes: 365 additions & 0 deletions t_visa_trends_team1/Deliverable 1/t-visa trend.ipynb
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"import numpy as np\n",
"import pandas as pd"
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" <th>file_name</th>\n",
" <th>ID</th>\n",
" <th>date</th>\n",
" <th>decision</th>\n",
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" <td>Form I-914, Application for T Nonimmigrant Status</td>\n",
" <td>The decision of the Director is withdrawn.</td>\n",
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" ID date decision \\\n",
"0 9044770 SEP172020 Appeal of Vermont Service Center Decision \n",
"1 6288405 SEP172020 Appeal of Vermont Service Center Decision \n",
"2 6500174 SEP112020 Appeal of Vermont Service Center Decision \n",
"3 6431583 SEP092020 Appeal of Vermont Service Center Decision \n",
"4 6479121 SEP092020 Appeal of Vermont Service Center Decision \n",
"\n",
" status \\\n",
"0 Form I-914, Application for T Nonimmigrant Status \n",
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"We collected a 188 rows, 9 columns dataset from [non-precedent decisions](https://www.uscis.gov/administrative-appeals/aao-decisions/aao-non-precedent-decisions) (search \"Form I-914\")\n"
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"(188, 9)"
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"The appeal is dismissed. 138\n",
"The decision of the Director is withdrawn. 16\n",
"The motion to reopen is denied. 13\n",
"The motion to reconsider is dismissed. 6\n",
"The appeal is rejected. 3\n",
"The motion to reopen is granted. 2\n",
"The matter is remanded for the entry of a new decision consistent with the foregoing analysis, which, if adverse, shall be certified to us for review. 1\n",
"The motion to reconsider is denied. 1\n",
"The appeal is sustained. 1\n",
"The initial decision of the Director, Vermont Service Center, is withdrawn. 1\n",
"The application is denied. 1\n",
"The application is dismissed. 1\n",
"The appeal is dismisse. 1\n",
"The motion to reopen is dismissed. 1\n",
"The initial decision of the Director, Vermont Service Center, dated November 21, 2014, is affirmed, and the application is denied. 1\n",
"The appeal is summarily dismissed pursuant to 8 C. 1\n",
"Name: order, dtype: int64"
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"source": [
"According to the data, we can see 138 cases are dismissed, 16 cases are withdrawn, and etc...\n",
"\n",
"However, before we can answer questions from clients properly, we need to understand these statements properly then process the data set. We will discuss it during this Friday client meeting. "
]
},
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17 changes: 17 additions & 0 deletions t_visa_trends_team1/scrum_1.md
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# 10/16 Meeting

What have I worked on?

- Use python package scrapy to crawl all pdf links to the Non-precedent decisions, and save these links into a single txt file.

What will I be working on next?

- We decided to work with team 2 together to collect dataset since at this stage, most of our work are the same, so we don't want to waste time. For next week, we will try to download these files by years, and convert them into txt file.

Have I run into any issues? Do I need help?

- I didn't think we run into any issues at this stage. All we need to do is to sure we will not miss any links during scraping.

Have I talked to the client recently? When are we meeting with them next?

- We plan to meet PM weekly so we can keep on the right track. The representative of client will show up as well.
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