In previous posts I have demonstrated how you can query stock price data with e.g. pandas_datareader in Python. In this post I will present an algorithm with which you can construct an efficient portfolio based on any set of stocks […]
In other posts I have demonstrated how one can use quandl in Python to query time series data on e.g. equity prices. In this post I demonstrate how one can query stock price data from e.g. Yahoo finance, using the […]
In previous posts I have demonstrated how one can geocode data and plot markers using Geopy and Folium in Python. I have also demonstrated heatmapping workflows in R, using packages such as Leaflet. In this post I want to use […]
In a previous post I have already demonstrated how to use Nominatim in Python (using the Geopy module) to geocode a location name into longitude and latitude coordinates. In this post I want to show how one can geocode a […]
A quick post on how to query data from Quandl in Python. Quandl can be installed with the “pip install” command in your command prompt. For this simply type “pip install quandl” in your Anaconda command prompt. Quandl is the […]
Besides Pandas and Seaborn I would also like to provide you with a brief introduction to matplotlib. Matplotlib is another important module and library in Python. It is used for data visualization. Below coding example will get you started. The […]
This post is a rough introduction to the Seaborn module in Python. I use it for data visualization, in combination with Pandas. Read the comments to understand my workflow. Any questions you can leave as a comment at the bottom […]
This is an introduction to the Pandas module in Python. I demonstrate core Pandas functionality using a tabular dataset from OICA. # import pandas import pandas # read in oica.csv file with data pandas.read_csv(“oica.csv”,sep=”,”) year country output 0 2018 Argentina […]
