marsja / jupyter Goto Github PK

Repository containing Jupyter Notebooks for most of the blog posts on my blog. For example, there are data visualization, data manipulation, and data analysis code examples in the Notebooks

Home Page: https://www.marsja.se

Jupyter Notebook 100.00%

jupyter-notebooks pandas-dataframe-tutorial repeated-measures-anova anova rpy2 data-visualization rpy2-tutorial

jupyter's Introduction

Jupyter notebooks

In this folder you will find Jupyter Notebooks containing code examples for many of my blogposts (https://www.marsja.se). There are also notebooks containing the code for some of my Videos on my YouTube Channel. The main theme of the blog posts, right now, is data visualization, manipulation, and analysis using Python. For instance, you will find Pandas tutorials, Seaborn tutorials, and Statsmodels tutorials (e.g., Python ANOVA).

Pandas DataFrame Tutorial: Jupyter Notebooks

Here are different Notebooks containing the code examples for some of the Pandas Tutorials:

Reversing Pandas Dataframe
Pandas Dataframe Tutorial: Working with Dataframes
Python Pandas JSON Tutorial
Data Cleansing With Pandas and Pyjanitor - In this notebook code examples on how to delete missing values, remove empty columns, clean column names (i.e., rename columns) and so on can be found.
Read SPSS files in Python - Learn how to load .sav files into Pandas dataframes.
Converting a Dictionary to a Pandas Dataframe
How to Print the Columns Names in a Pandas dataframe

Working with DataFrame

Here you will find Jupyter notebooks, both R and Python right now, that focuses on how to work with data in specific ways.

How to Reverse Code in R - An R note book for learning how to reverse scores from a questionnaire using R and the package psych. -Create Dummy Variables in Python with Pandas

Data Visualization in Python: Code Examples

Note books for different Data Visualization Tutorials:

Kernel Estimation, Cumulative Distribution Function, Delta Plot, & Conditional Accuracy Function: Different data visualization techniques for response time data
Python Data Visualization Tutorial: How to Create a Scatter Plot
How to Make Scatter Plots using Python - Here we work with the following Seaborn methods: scatterplot, regplot, lmpot, and pairplot. We learn how to make scatter plots with regression lines, change the color and markers of Seaborn plots, rotate the ticks labels, and much more.
Raincloud Plots in Python Here's the example code from the Python data visualization tutorial on how to make raincloud plots in Python (YouTube Video)
How to make a Histogram in Python with Pandas

Data Visualization in R: Code examples

Scatterplots in R using ggplot2 - Notebook containing code examples on how to create scatter plots using ggplot2.

Rpy2 Tutorial: Code Examples

For some data analysis techniques we may want to use R. This because it may not yet be implemented in Python. Here are some Jupyter Notebooks for one Python package called Rpy2:

Rpy2 & R-plots in Jupyter Notebooks (See the YouTube Video)
Rpy2 Tutorial: Example

Python Data Analysis Tutorials

In this section, we find the code examples, in the form of Jupyter Notebooks, for the Python data analysis tutorials;

Descriptive Statistics in Python

Here, there are some Jupyter Notebooks for carrying out summary statistics using Python, Pandas, Scipy, and other useful Python packages

T-test

Two-Sample T-test in Python

ANOVA in Python and R

Here we have Python ANOVA Notebooks. There is also one Notebook for carrying out ANOVA using R.

Python ANOVA (Between Groups)

Python ANOVA (Within Group)

MANOVA in Python

One-Way MANOVA using Statsmodels - This notebook contains the multivariate data analysis Multivariate Analysis of Variance (MANOVA)

Other

Tutorials, guides, and how tos (both Python and R) that doesn't fit into the above categories

Get Max Value in Dictionary in Python
Convert HTML to Jupyter notebook - Code to convert HTML (e.g., code within code tags) to .ipynb files that can be run
Convert Float Array to Integer Array Python - Code to convert a NumPy float Array to an Integer Array

jupyter's People

Stargazers

Watchers

Forkers

ksuljic ali-nayeem sealtamirano msuryaprakash grantxie528 irdaraujo nunuse hidayatarg weizhiting kbility beargii davidbestue naturallyash fethsc vds-tanuj4567 r4rahman jessezhangye ghost1141649324 aefabris zizhangchen lakshmisay campusge grandgrandgrand ckaelig priya-gittest shalevy1 muratcemkose iago-noncontributedforks datasummer19 chitranshp redtailcatfish wowothk gridl zhiyun2809 arefamirreza wkenro elsenra gitter-badger anazjosh suryansh2020 pfbalan amolgbakane beto3110 ja-drive fedjap preethamalluri 48120778 samuelmiver manugent samstaps mathang dancampos1 laoqingshuqiang kswain1 tarungoel otemay hotgly justinm0rgan akone19a brainclone ntirandaz hankrobot lsvz hxb087 oscar-gr anunda-nyagami mkaanarici baluvanan nadiacandoit jmcastagnini priyanshu-sahu wlm2019 rahulbiswas24680 luisgomes24 40015569 richlysakowski yon23 ajscriv 123mame huazai-beyond121 rodski galibce003 congltk1234 g-i-o-r-g-i-o yiyangzhang0201 n-e1 jellis-ventiv danielsywang dhawal93 hediatnani mmdcocosta prashantloni9164 joseph-waru djintomank heartofswine gjuri abrahim-bamatraf gaurav19999 adebisae simplebutcomplex

jupyter's Issues

Scraper is broken "How to Convert Python HTML to Jupyter NB" references a missing tag... https://github.com/marsja/jupyter/blob/master/convert_html_jupyter_notebook_tutorial.ipynb

The example on the website below does not work, because the article calls out a tag "post-content" that does not exist in the WordPress page.

The example does not scrape anything because "post-content" is missing from the Response object. The result of the "get_data()" function is a None object.

https://www.marsja.se/converting-html-to-a-jupyter-notebook/
https://github.com/marsja/jupyter/blob/master/convert_html_jupyter_notebook_tutorial.ipynb

The article needs to be updated so that the scraper actually works.

Here's where the article references the tag to parse.

5. Getting the Code Elements from the HTML

In the last step, we are creating a Python function called get_code. This function will take two arguments. First, the beautifulsoup object, we earlier created, and the content_class to search for content in. In the case, of this particular WordPress, blog this will be "post-content"

rpy2: unable to install packages

File: rpy2 tutorial example code.ipynb

This bit of code:

packageNames = ('afex', 'emmeans')
utils = rpackages.importr('utils')
utils.chooseCRANmirror(ind=1)

packnames_to_install = [x for x in packageNames if not rpackages.isinstalled(x)]

if len(packnames_to_install) > 0:
    utils.install_packages(StrVector(packnames_to_install))

results in this error:

R[write to console]: Installing packages into ‘/usr/local/lib/R/site-library’
(as ‘lib’ is unspecified)

R[write to console]: Warning in (function (pkgs, lib, repos = getOption("repos"), contriburl = contrib.url(repos,  :
R[write to console]: 
 
R[write to console]:  'lib = "/usr/local/lib/R/site-library"' is not writable

R[write to console]: Error in (function (pkgs, lib, repos = getOption("repos"), contriburl = contrib.url(repos,  : 
  unable to install packages

R[write to console]: In addition: 
R[write to console]: Warning messages:

R[write to console]: 1: 
R[write to console]: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE,  :
R[write to console]: 
 
R[write to console]:  libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages

R[write to console]: 2: 
R[write to console]: In (function (package, help, pos = 2, lib.loc = NULL, character.only = FALSE,  :
R[write to console]: 
 
R[write to console]:  libraries ‘/usr/local/lib/R/site-library’, ‘/usr/lib/R/site-library’ contain no packages

---------------------------------------------------------------------------
RRuntimeError                             Traceback (most recent call last)
<ipython-input-13-8999ff1bff9e> in <module>
      6 
      7 if len(packnames_to_install) > 0:
----> 8     utils.install_packages(StrVector(packnames_to_install))

/opt/anaconda3/lib/python3.7/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    190                 kwargs[r_k] = v
    191         return (super(SignatureTranslatedFunction, self)
--> 192                 .__call__(*args, **kwargs))
    193 
    194 

/opt/anaconda3/lib/python3.7/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
    119             else:
    120                 new_kwargs[k] = conversion.py2rpy(v)
--> 121         res = super(Function, self).__call__(*new_args, **new_kwargs)
    122         res = conversion.rpy2py(res)
    123         return res

/opt/anaconda3/lib/python3.7/site-packages/rpy2/rinterface_lib/conversion.py in _(*args, **kwargs)
     26 def _cdata_res_to_rinterface(function):
     27     def _(*args, **kwargs):
---> 28         cdata = function(*args, **kwargs)
     29         # TODO: test cdata is of the expected CType
     30         return _cdata_to_rinterface(cdata)

/opt/anaconda3/lib/python3.7/site-packages/rpy2/rinterface.py in __call__(self, *args, **kwargs)
    771                     error_occured))
    772             if error_occured[0]:
--> 773                 raise embedded.RRuntimeError(_rinterface._geterrmessage())
    774         return res
    775 

RRuntimeError: Error in (function (pkgs, lib, repos = getOption("repos"), contriburl = contrib.url(repos,  : 
  unable to install packages