added sentiment analysis using vader tutorial

Author: x4nth055

README.md

@@ -35,6 +35,7 @@ This is a repository of all the tutorials of [The Python Code](https://www.thepy
         - [How to Build a Spam Classifier using Keras in Python](https://www.thepythoncode.com/article/build-spam-classifier-keras-python). ([code](machine-learning/nlp/spam-classifier))
         - [How to Build a Text Generator using TensorFlow and Keras in Python](https://www.thepythoncode.com/article/text-generation-keras-python). ([code](machine-learning/nlp/text-generator))
         - [How to Perform Text Classification in Python using Tensorflow 2 and Keras](https://www.thepythoncode.com/article/text-classification-using-tensorflow-2-and-keras-in-python). ([code](machine-learning/nlp/text-classification))
+        - [Sentiment Analysis using Vader in Python](https://www.thepythoncode.com/article/vaderSentiment-tool-to-extract-sentimental-values-in-texts-using-python). ([code](machine-learning/nlp/sentiment-analysis-vader))
     - ### [Computer Vision](https://www.thepythoncode.com/topic/computer-vision)
         - [How to Detect Human Faces in Python using OpenCV](https://www.thepythoncode.com/article/detect-faces-opencv-python). ([code](machine-learning/face_detection))
         - [How to Make an Image Classifier in Python using TensorFlow and Keras](https://www.thepythoncode.com/article/image-classification-keras-python). ([code](machine-learning/image-classifier))

machine-learning/nlp/sentiment-analysis-vader/README.md

@@ -0,0 +1,2 @@
+# [Sentiment Analysis using Vader in Python](https://www.thepythoncode.com/article/vaderSentiment-tool-to-extract-sentimental-values-in-texts-using-python)
+- `pip3 install -r requirements.txt`

machine-learning/nlp/sentiment-analysis-vader/requirements.txt

@@ -0,0 +1 @@
+vaderSentiment

machine-learning/nlp/sentiment-analysis-vader/sentiment_analysis.py

@@ -0,0 +1,25 @@
+from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+
+# init the sentiment analyzer
+sia = SentimentIntensityAnalyzer()
+
+sentences = [
+    "This food is amazing and tasty !",
+    "Exoplanets are planets outside the solar system",
+    "This is sad to see such bad behavior"
+]
+
+for sentence in sentences:
+    score = sia.polarity_scores(sentence)["compound"]
+    print(f'The sentiment value of the sentence :"{sentence}" is : {score}')
+
+for sentence in sentences:
+    print(f'For the sentence "{sentence}"')
+    polarity = sia.polarity_scores(sentence)
+    pos = polarity["pos"]
+    neu = polarity["neu"]
+    neg = polarity["neg"]
+    print(f'The percententage of positive sentiment in :"{sentence}" is : {round(pos*100,2)} %')
+    print(f'The percententage of neutral sentiment in :"{sentence}" is : {round(neu*100,2)} %')
+    print(f'The percententage of negative sentiment in :"{sentence}" is : {round(neg*100,2)} %')
+    print("="*50)