INST728E - HW1

Run this file to make sure all the packages in your environment are set up correctly.

Also, fill out the fields below.

In [ ]:
print("My Name Is: <YOUR NAME>")
print("My Email Is: <YOUR EMAIL>")

Standard Libraries for Graphing and Numbers

Installed via pip install matplotlib numpy pandas

In [ ]:
# Matplotlib Graphing Library
import matplotlib
import matplotlib.pyplot as plt

# Numpy for fast numeric computation
import numpy as np

# Pandas for R-like DataFrames
import pandas as pd

Networking/Web Scraping Library

Installed via pip install requests

In [ ]:
# Library for issueing human-readable requests to HTTP servers
import requests

Libraries for Social Networking APIs

Installed via pip install facebook-sdk praw tweepy

In [ ]:
# Facebook-SDK Library
import facebook

# Reddit's Python API Wrapper
import praw

# Twitter + Python API Wrapper
import tweepy

Geospatial Package for Building Maps

Installed via conda install -c conda-forge basemap basemap-data-hires

In [ ]:
from mpl_toolkits.basemap import Basemap

Scikit Package for Machine Learning and Feature Extraction

Installed via pip install scipy sklearn

In [ ]:
import sklearn.cluster
import sklearn.feature_extraction 
import sklearn.feature_extraction.text
import sklearn.metrics
import sklearn.preprocessing

Text Processing Libraries

Installed via pip install nltk textblob gensim

In [ ]:
# NLTK, the Natural Language Toolkit
import nltk
import nltk.sentiment.util
import nltk.sentiment.vader
from nltk.corpus import stopwords
from nltk.tokenize import TweetTokenizer
In [ ]:
# Go ahead and download standard lexica"stopwords") # For removing "and", "or", "the", etc."vader_lexicon") # For Twitter-centric sentiment analysis
In [ ]:
# High-level Package for Text Analysis, relies on NLTK
from textblob import TextBlob
In [ ]:
# Fast library for topic modeling
from gensim import matutils
from gensim.models import ldamulticore
from gensim.corpora import Dictionary
from gensim.models import TfidfModel
from gensim.models import atmodel
from gensim.models.phrases import Phrases

Network Analysis Library

Installed via pip install networkx

In [ ]:
import networkx as nx
In [ ]: