test

atqy · Oct 27, 2022 · 05092ae · 05092ae
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diff --git a/...gest-data-types/ingest_tabular_data.ipynb → ...ta-types/ingest_tabular_data_rename.ipynb b/...gest-data-types/ingest_tabular_data.ipynb → ...ta-types/ingest_tabular_data_rename.ipynb
@@ -200,25 +200,6 @@
     "with fs.open(data_s3fs_location) as f:\n",
     "    print(pd.read_csv(f, nrows=5))"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### 3.2 AWS Data Wrangler\n",
-    "[AWS Data Wrangler](https://github.com/awslabs/aws-data-wrangler) is an open-source Python library that extends the power of the Pandas library to AWS connecting DataFrames and AWS data related services (Amazon Redshift, AWS Glue, Amazon Athena, Amazon EMR, Amazon QuickSight, etc), which we will cover in later sections. It is built on top of other open-source projects like Pandas, Apache Arrow, Boto3, s3fs, SQLAlchemy, Psycopg2 and PyMySQL, and offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses and Databases. Note that you would need `s3fs version > 0.4.0` for the `awswrangler csv reader` to work."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "data_wr_location = \"s3://{}/{}/{}\".format(bucket, prefix, filename)  # S3 URL\n",
-    "wr_data = wr.s3.read_csv(path=data_wr_location, nrows=5)\n",
-    "wr_data.head()"
-   ]
   }
  ],
  "metadata": {

diff --git a/.../ingest-data-types/ingest_text_data.ipynb → ...-data-types/ingest_text_data_rename.ipynb b/.../ingest-data-types/ingest_text_data.ipynb → ...-data-types/ingest_text_data_rename.ipynb
@@ -480,18 +480,6 @@
     "text_data_new.to_csv(filename, index=False)\n",
     "upload_to_s3(bucket, \"text_twitter_sentiment_full\", filename)"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Citation\n",
-    "Twitter140 Data, Go, A., Bhayani, R. and Huang, L., 2009. Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford, 1(2009), p.12.\n",
-    "\n",
-    "SMS Spaming data, Almeida, T.A., Gómez Hidalgo, J.M., Yamakami, A. Contributions to the Study of SMS Spam Filtering: New Collection and Results.  Proceedings of the 2011 ACM Symposium on Document Engineering (DOCENG'11), Mountain View, CA, USA, 2011.\n",
-    "\n",
-    "J! Archive, J! Archive is created by fans, for fans. The Jeopardy! game show and all elements thereof, including but not limited to copyright and trademark thereto, are the property of Jeopardy Productions, Inc. and are protected under law. This website is not affiliated with, sponsored by, or operated by Jeopardy Productions, Inc."
-   ]
   }
  ],
  "metadata": {

diff --git a/...ist/pytorch_mnist_elastic_inference.ipynb → ...orch_mnist_elastic_inference_rename.ipynb b/...ist/pytorch_mnist_elastic_inference.ipynb → ...orch_mnist_elastic_inference_rename.ipynb