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‎.nojekyll

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‎modules/week02/index-02.html

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<section id="cleaning-the-raw-data" class="level2">
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<h2 class="anchored" data-anchor-id="cleaning-the-raw-data">Cleaning the raw data</h2>
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<p>The original shorebird data set has been collected over many years by many different researchers. It is thus prone to have some data quality issues. Before we can ingest our data into our database, we will have to implement some data cleaning on the csv files to make sure we do not loose information during the import due to the constraints we can impose on the database. And in any case, the <code>garbage in, garbage out</code> motto often use in modeling applies here as well!</p>
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<p>Here is the repository where we are going to practice our data wranglers skills:</p>
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<p>Here is the repository where we are going to practice our data wranglers skills, <strong>PLEASE CREATE A FORK and clone your fork to your machine</strong>:</p>
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<p><a href="https://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning" class="uri">https://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning</a></p>
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<section id="analyzing-the-data-from-the-csv-files" class="level2">

‎search.json

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"text": "The original shorebird data set has been collected over many years by many different researchers. It is thus prone to have some data quality issues. Before we can ingest our data into our database, we will have to implement some data cleaning on the csv files to make sure we do not loose information during the import due to the constraints we can impose on the database. And in any case, the garbage in, garbage out motto often use in modeling applies here as well!\nHere is the repository where we are going to practice our data wranglers skills:\nhttps://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning"
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"text": "The original shorebird data set has been collected over many years by many different researchers. It is thus prone to have some data quality issues. Before we can ingest our data into our database, we will have to implement some data cleaning on the csv files to make sure we do not loose information during the import due to the constraints we can impose on the database. And in any case, the garbage in, garbage out motto often use in modeling applies here as well!\nHere is the repository where we are going to practice our data wranglers skills, PLEASE CREATE A FORK and clone your fork to your machine:\nhttps://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning"
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"text": "The original shorebird data set has been collected over many years by many different researchers. It is thus prone to have some data quality issues. Before we can ingest our data into our database, we will have to implement some data cleaning on the csv files to make sure we do not loose information during the import due to the constraints we can impose on the database. And in any case, the garbage in, garbage out motto often use in modeling applies here as well!\nHere is the repository where we are going to practice our data wranglers skills:\nhttps://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning"
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"text": "The original shorebird data set has been collected over many years by many different researchers. It is thus prone to have some data quality issues. Before we can ingest our data into our database, we will have to implement some data cleaning on the csv files to make sure we do not loose information during the import due to the constraints we can impose on the database. And in any case, the garbage in, garbage out motto often use in modeling applies here as well!\nHere is the repository where we are going to practice our data wranglers skills, PLEASE CREATE A FORK and clone your fork to your machine:\nhttps://github.com/UCSB-Library-Research-Data-Services/bren-meds213-data-cleaning"
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