Python

Want to learn Data Science and Python?

February 19, 2020 By admin

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Scrapy: Python Web-scaping Framework

October 30, 2019 By admin

Scrapy is a fast high-level web crawling and web scraping framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. Getting help Having trouble? We’d like to help! Try the FAQ – it’s got answers to some common questions. Looking for […]

Natural Language Toolkit

October 25, 2019 By admin

NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries, and an active discussion forum. Thanks to […]

10 minutes to pandas python data analysis toolkit

October 25, 2019 By admin

This is a short introduction to pandas, geared mainly for new users. You can see more complex recipes in the Cookbook. Customarily, we import as follows:

<strong>In [1]: </strong><strong>import</strong> <strong>numpy</strong> <strong>as</strong> <strong>np</strong>

<strong>In [2]: </strong><strong>import</strong> <strong>pandas</strong> <strong>as</strong> <strong>pd</strong>

In [1]: import numpy as np

In [2]: import pandas as pd

Object creation See the Data Structure Intro section. Creating a Series by passing a list of values, letting pandas create a default integer index:

<strong>In [3]: </strong>s = pd.Series([1, 3, 5, np.nan, 6, 8])

<strong>In [4]: </strong>s
<strong>Out[4]: </strong>
0    1.0
1    3.0
2    5.0
3    NaN
4    6.0
5    8.0
dtype: float64

In [3]: s = pd.Series([1, 3, 5, np.nan, 6, 8])

In [4]: s

Out[4]:

0 1.0

1 3.0

2 5.0

3 NaN

4 6.0

5 8.0

dtype: float64

Creating a DataFrame by passing a NumPy array, with […]

Python Numpy Tutorial

October 24, 2019 By admin

This tutorial was contributed by Justin Johnson. We will use the Python programming language for all assignments in this course. Python is a great general-purpose programming language on its own, but with the help of a few popular libraries (numpy, scipy, matplotlib) it becomes a powerful environment for scientific computing. We expect that many of you […]