diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 00000000..16a6ff15
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+*.txt filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
index b56837d9..7fbb9640 100644
--- a/.gitignore
+++ b/.gitignore
@@ -23,6 +23,11 @@ db.sqlite3-journal
 # in your Git repository. Update and uncomment the following line accordingly.
 # <django-project-name>/staticfiles/
 
+## Data Science
+datascience/price-volume-data-for-all-us-stocks-etfs/
+
+
+
 ### Django.Python Stack ###
 # Byte-compiled / optimized / DLL files
 *.py[cod]
@@ -726,4 +731,4 @@ MigrationBackup/
 
 # End of https://www.gitignore.io/api/go,xcode,swift,flask,django,python,firebase,cocoapods,visualstudio,jupyternotebooks,visualstudiocode
 .DS_Store
-.vscode
\ No newline at end of file
+.vscode
diff --git a/.gitignore.swp b/.gitignore.swp
new file mode 100644
index 00000000..89c9ba9e
Binary files /dev/null and b/.gitignore.swp differ
diff --git a/Pipfile b/Pipfile
new file mode 100644
index 00000000..c8d501ef
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,12 @@
+[[source]]
+name = "pypi"
+url = "https://pypi.org/simple"
+verify_ssl = true
+
+[dev-packages]
+
+[packages]
+yfinance = "*"
+
+[requires]
+python_version = "3.7"
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 00000000..26d34309
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,135 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "ae7e7d1aff93439f6e642e763ffd526dbd1554cf09332c4b90b980b52d3a022c"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.7"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {
+        "certifi": {
+            "hashes": [
+                "sha256:017c25db2a153ce562900032d5bc68e9f191e44e9a0f762f373977de9df1fbb3",
+                "sha256:25b64c7da4cd7479594d035c08c2d809eb4aab3a26e5a990ea98cc450c320f1f"
+            ],
+            "version": "==2019.11.28"
+        },
+        "chardet": {
+            "hashes": [
+                "sha256:84ab92ed1c4d4f16916e05906b6b75a6c0fb5db821cc65e70cbd64a3e2a5eaae",
+                "sha256:fc323ffcaeaed0e0a02bf4d117757b98aed530d9ed4531e3e15460124c106691"
+            ],
+            "version": "==3.0.4"
+        },
+        "idna": {
+            "hashes": [
+                "sha256:7588d1c14ae4c77d74036e8c22ff447b26d0fde8f007354fd48a7814db15b7cb",
+                "sha256:a068a21ceac8a4d63dbfd964670474107f541babbd2250d61922f029858365fa"
+            ],
+            "version": "==2.9"
+        },
+        "multitasking": {
+            "hashes": [
+                "sha256:b59d99f709d2e17d60ccaa2be09771b6e9ed9391c63f083c0701e724f624d2e0"
+            ],
+            "version": "==0.0.9"
+        },
+        "numpy": {
+            "hashes": [
+                "sha256:1786a08236f2c92ae0e70423c45e1e62788ed33028f94ca99c4df03f5be6b3c6",
+                "sha256:17aa7a81fe7599a10f2b7d95856dc5cf84a4eefa45bc96123cbbc3ebc568994e",
+                "sha256:20b26aaa5b3da029942cdcce719b363dbe58696ad182aff0e5dcb1687ec946dc",
+                "sha256:2d75908ab3ced4223ccba595b48e538afa5ecc37405923d1fea6906d7c3a50bc",
+                "sha256:39d2c685af15d3ce682c99ce5925cc66efc824652e10990d2462dfe9b8918c6a",
+                "sha256:56bc8ded6fcd9adea90f65377438f9fea8c05fcf7c5ba766bef258d0da1554aa",
+                "sha256:590355aeade1a2eaba17617c19edccb7db8d78760175256e3cf94590a1a964f3",
+                "sha256:70a840a26f4e61defa7bdf811d7498a284ced303dfbc35acb7be12a39b2aa121",
+                "sha256:77c3bfe65d8560487052ad55c6998a04b654c2fbc36d546aef2b2e511e760971",
+                "sha256:9537eecf179f566fd1c160a2e912ca0b8e02d773af0a7a1120ad4f7507cd0d26",
+                "sha256:9acdf933c1fd263c513a2df3dceecea6f3ff4419d80bf238510976bf9bcb26cd",
+                "sha256:ae0975f42ab1f28364dcda3dde3cf6c1ddab3e1d4b2909da0cb0191fa9ca0480",
+                "sha256:b3af02ecc999c8003e538e60c89a2b37646b39b688d4e44d7373e11c2debabec",
+                "sha256:b6ff59cee96b454516e47e7721098e6ceebef435e3e21ac2d6c3b8b02628eb77",
+                "sha256:b765ed3930b92812aa698a455847141869ef755a87e099fddd4ccf9d81fffb57",
+                "sha256:c98c5ffd7d41611407a1103ae11c8b634ad6a43606eca3e2a5a269e5d6e8eb07",
+                "sha256:cf7eb6b1025d3e169989416b1adcd676624c2dbed9e3bcb7137f51bfc8cc2572",
+                "sha256:d92350c22b150c1cae7ebb0ee8b5670cc84848f6359cf6b5d8f86617098a9b73",
+                "sha256:e422c3152921cece8b6a2fb6b0b4d73b6579bd20ae075e7d15143e711f3ca2ca",
+                "sha256:e840f552a509e3380b0f0ec977e8124d0dc34dc0e68289ca28f4d7c1d0d79474",
+                "sha256:f3d0a94ad151870978fb93538e95411c83899c9dc63e6fb65542f769568ecfa5"
+            ],
+            "version": "==1.18.1"
+        },
+        "pandas": {
+            "hashes": [
+                "sha256:23e177d43e4bf68950b0f8788b6a2fef2f478f4ec94883acb627b9264522a98a",
+                "sha256:2530aea4fe46e8df7829c3f05e0a0f821c893885d53cb8ac9b89cc67c143448c",
+                "sha256:303827f0bb40ff610fbada5b12d50014811efcc37aaf6ef03202dc3054bfdda1",
+                "sha256:3b019e3ea9f5d0cfee0efabae2cfd3976874e90bcc3e97b29600e5a9b345ae3d",
+                "sha256:3c07765308f091d81b6735d4f2242bb43c332cc3461cae60543df6b10967fe27",
+                "sha256:5036d4009012a44aa3e50173e482b664c1fae36decd277c49e453463798eca4e",
+                "sha256:6f38969e2325056f9959efbe06c27aa2e94dd35382265ad0703681d993036052",
+                "sha256:74a470d349d52b9d00a2ba192ae1ee22155bb0a300fd1ccb2961006c3fa98ed3",
+                "sha256:7d77034e402165b947f43050a8a415aa3205abfed38d127ea66e57a2b7b5a9e0",
+                "sha256:7f9a509f6f11fa8b9313002ebdf6f690a7aa1dd91efd95d90185371a0d68220e",
+                "sha256:942b5d04762feb0e55b2ad97ce2b254a0ffdd344b56493b04a627266e24f2d82",
+                "sha256:a9fbe41663416bb70ed05f4e16c5f377519c0dc292ba9aa45f5356e37df03a38",
+                "sha256:d10e83866b48c0cdb83281f786564e2a2b51a7ae7b8a950c3442ad3c9e36b48c",
+                "sha256:e2140e1bbf9c46db9936ee70f4be6584d15ff8dc3dfff1da022d71227d53bad3"
+            ],
+            "version": "==1.0.1"
+        },
+        "python-dateutil": {
+            "hashes": [
+                "sha256:73ebfe9dbf22e832286dafa60473e4cd239f8592f699aa5adaf10050e6e1823c",
+                "sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a"
+            ],
+            "version": "==2.8.1"
+        },
+        "pytz": {
+            "hashes": [
+                "sha256:1c557d7d0e871de1f5ccd5833f60fb2550652da6be2693c1e02300743d21500d",
+                "sha256:b02c06db6cf09c12dd25137e563b31700d3b80fcc4ad23abb7a315f2789819be"
+            ],
+            "version": "==2019.3"
+        },
+        "requests": {
+            "hashes": [
+                "sha256:43999036bfa82904b6af1d99e4882b560e5e2c68e5c4b0aa03b655f3d7d73fee",
+                "sha256:b3f43d496c6daba4493e7c431722aeb7dbc6288f52a6e04e7b6023b0247817e6"
+            ],
+            "version": "==2.23.0"
+        },
+        "six": {
+            "hashes": [
+                "sha256:236bdbdce46e6e6a3d61a337c0f8b763ca1e8717c03b369e87a7ec7ce1319c0a",
+                "sha256:8f3cd2e254d8f793e7f3d6d9df77b92252b52637291d0f0da013c76ea2724b6c"
+            ],
+            "version": "==1.14.0"
+        },
+        "urllib3": {
+            "hashes": [
+                "sha256:2f3db8b19923a873b3e5256dc9c2dedfa883e33d87c690d9c7913e1f40673cdc",
+                "sha256:87716c2d2a7121198ebcb7ce7cccf6ce5e9ba539041cfbaeecfb641dc0bf6acc"
+            ],
+            "version": "==1.25.8"
+        },
+        "yfinance": {
+            "hashes": [
+                "sha256:cee223cbd31e14955869f7978bcf83776d644345c7dea31ba5d41c309bfb0d3d"
+            ],
+            "index": "pypi",
+            "version": "==0.1.54"
+        }
+    },
+    "develop": {}
+}
diff --git a/datascience/Bitcoin Price Prediction Model.ipynb b/datascience/Bitcoin Price Prediction Model.ipynb
deleted file mode 100644
index 1fcd516a..00000000
--- a/datascience/Bitcoin Price Prediction Model.ipynb	
+++ /dev/null
@@ -1,41 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "print('hello world')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.6-final"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
\ No newline at end of file
diff --git a/datascience/LSTM-Model.ipynb b/datascience/LSTM-Model.ipynb
new file mode 100644
index 00000000..a4d5322d
--- /dev/null
+++ b/datascience/LSTM-Model.ipynb
@@ -0,0 +1,111 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Long Short-Term Memory networks in python are good tools to make stock market predictions\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/pandas_datareader/compat/__init__.py:7: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
+      "  from pandas.util.testing import assert_frame_equal\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:526: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:527: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:528: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:529: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:530: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
+      "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:535: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
+      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pandas_datareader import data\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import datetime as dt\n",
+    "import urllib.request, json\n",
+    "import os\n",
+    "import numpy as np\n",
+    "import tensorflow as tf # This code has been tested with TensorFlow 1.6\n",
+    "from sklearn.preprocessing import MinMaxScaler"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Download the Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Loaded data from the Kaggle repository\n"
+     ]
+    }
+   ],
+   "source": [
+    "data_source = 'kaggle' \n",
+    "\n",
+    "if data_source == 'alphavantage':\n",
+    "    api_key = 'IOLIXAXKGPI3A4QM'\n",
+    "    ticker = 'AAL' # american airlines\n",
+    "    \n",
+    "else:\n",
+    "    df = pd.read_csv(('price-volume-data-for-all-us-stocks-etfs/Stocks/aal.us.txt'), delimiter=',', usecols=['Date','Open','High','Low','Close'])\n",
+    "    print('Loaded data from the Kaggle repository')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/datascience/Stock-Prediction-Model.ipynb b/datascience/Stock-Prediction-Model.ipynb
index b1fdd5d9..8857aea6 100644
--- a/datascience/Stock-Prediction-Model.ipynb
+++ b/datascience/Stock-Prediction-Model.ipynb
@@ -61,19 +61,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
-     "ename": "AttributeError",
-     "evalue": "module 'numpy' has no attribute '__version__'",
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'quandl'",
      "output_type": "error",
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-9-bd4aa7bdbead>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mstocker\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mStocker\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/matplotlib/__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m    208\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 210\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcompare_versions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__version__\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m__version__numpy__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    211\u001b[0m     raise ImportError(\n\u001b[1;32m    212\u001b[0m         \"Matplotlib requires numpy>=%s; you have %s\" % (\n",
-      "\u001b[0;31mAttributeError\u001b[0m: module 'numpy' has no attribute '__version__'"
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-bd4aa7bdbead>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mstocker\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mStocker\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m~/Documents/Dev/Spyyder/datascience/stocker.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# Quandl for financial analysis, pandas and numpy for data manipulation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# fbprophet for additive models, #pytrends for Google trend data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mquandl\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'quandl'"
      ]
     }
    ],
@@ -451,7 +451,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.3"
   }
  },
  "nbformat": 4,
diff --git a/datascience/spacy_summarization.py b/datascience/spacy_summarization.py
index cb53fc13..98ad5ae6 100644
--- a/datascience/spacy_summarization.py
+++ b/datascience/spacy_summarization.py
@@ -1,3 +1,4 @@
+''' Text Summarizer using an ML library '''
 import spacy 
 nlp = spacy.load('en_core_web_sm')
 
diff --git a/datascience/trading-bot/Untitled.ipynb b/datascience/trading-bot/Untitled.ipynb
deleted file mode 100644
index 7fec5150..00000000
--- a/datascience/trading-bot/Untitled.ipynb
+++ /dev/null
@@ -1,6 +0,0 @@
-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/tf.py b/tf.py
new file mode 100644
index 00000000..9317b6ea
--- /dev/null
+++ b/tf.py
@@ -0,0 +1,9 @@
+import yfinance as yf
+
+
+msft = yf.Ticker('MSFT')
+#print(msft)
+
+#print(msft.previousClose)
+
+print(msft.history(period='max'))
\ No newline at end of file