📓
Dataprocessing
  • Preface
  • Essential Libraries
  • Introduction
  • Tidy data
  • Vectorized solutions
  • Load data
    • CSV
    • XML
    • SQL
    • json
  • Data Inspection
    • Dealing with missing values
    • Cleaning data
    • Normalization
  • Data Preparation
    • Tidy data
    • Combine data
    • Reshaping
      • Reshape with melt
  • Data exploration
  • Data visualisation
    • Panel basics
  • Plotten van kaarten
  • Data analysis
    • Statistics in Python
  • Databases
    • Database concepts
  • studycases
    • Montly sales data
      • Make it interactive using panel
    • Combine data to investigate a hypothesis
    • Twitter analysis using sql
  • Missing time related data
  • Plotting F1 race data
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  1. Load data

XML

eXtensible Markup Language

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Last updated 3 years ago

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XML is another common structured data format supporting hierarchal nested data with metadata. XML and HTML are structured similar but XML is more general. An example of XML is given below:

<CATALOG>
<PLANT>
        <COMMON>Bloodroot</COMMON>
        <BOTANICAL>Sanguinaria canadensis</BOTANICAL>
        <ZONE>4</ZONE>
        <LIGHT>Mostly Shady</LIGHT>
        <PRICE>$2.44</PRICE>
        <AVAILABILITY>031599</AVAILABILITY>
</PLANT>

Load XML

We can load the data by the read_xml() method. It parses the information directly in a DataFrame format

import pandas as pd
df = pd.read_xml('https://bioinf.nl/~fennaf/DSLS/plants.xml')
df.head()