Given an HTML table (code) in a file or at a given URL. First, load all HTML tables into the Python script by calling Pandas’ pd.read_html() passing the URL of the HTML document. The result is a list of DataFrames, one per HTML table in the document. Second, convert any specific DataFrame to a CSV … Read more
The Pandas read_html() function is an easy way to convert an HTML table (e.g., stored at a given URL) to a Pandas DataFrame. You pass a location string or path to it and it returns a list of DataFrames, each representing one table from the location path or URL. The following code, for example, reads … Read more
Problem Formulation and Solution Overview This article will show you how to access and retrieve tuple Elements from a List of Tuples in Python. 💡 Definition: Python Tuples are a type of Data Structure similar to Lists. However, Tuples are enclosed in round brackets () and are immutable, whereas Lists are enclosed in square brackets … Read more
What is KML? ℹ️ Definition: The Keyhole Markup Language (KML) is a file format for displaying geographic data in Google Earth or other so-called “Earth Browsers”. Similarly to XML, KML uses a tag-based structure with nested elements and attributes. How to Convert KML to CSV in Python? You can convert a .kml to a .csv … Read more
What is GeoJSON? 💡 GeoJSON is an RFC standardized data format to encode geographic data structures such as Point, LineString, Polygon, MultiPoint, MultiLineString, and MultiPolygon. GeoJSON is based on the JavaScript Object Notation (JSON). Example GeoJSON to CSV Say, you have the following GeoJSON snippet: You want to convert it to the following CSV format: … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to iterate over a 1D, 2D and 3D NumPy array using Python. When working with the NumPy library, you will encounter situations where you will need to iterate through a 1D, 2D and even a 3D array. This article will show you how to … Read more
What is a Fixed-Width File? 💡 Definition: A fixed-width text file contains data that is structured in rows and columns. Each row contains one data entry consisting of multiple values (one value per column). Each column has a fixed width, i.e., the same number of characters, restricting the maximum data size per column. Example of … Read more
Problem Formulation and Solution Overview In this article, you’ll learn how to check the Data Types of a Pandas Series. A Series is a 1D (one-dimensional) array. This Series can be of various data types, such as an integer, a string, a float or even an object! A good practice is to ensure, before performing … Read more
Problem Formulation Given a file my_file.dat like this one: How to convert this file to a CSV file of the following standard comma-separated values format: Method 1: Pandas Read and Write CSV You can convert a .dat file to a CSV file in Python in four simple steps: (1) Install the Pandas library, (2) import … Read more
Python Append Row to CSV To append a row (=dictionary) to an existing CSV, open the file object in append mode using open(‘my_file.csv’, ‘a’, newline=”). Then create a csv.DictWriter() to append a dict row using DictWriter.writerow(my_dict). Given the following file ‘my_file.csv’: You can append a row (dict) to the CSV file via this code snippet: … Read more
Method 1: CSV Writer To write a Python dictionary in a CSV file as a column, i.e., a single (key, value) pair per row, use the following three steps: Open the file in writing mode and using the newline=” argument to prevent blank lines. Create a CSV writer object. Iterate over the (key, value) pairs … Read more
To convert a Python dictionary to a CSV file with header, call the csv.DictWriter(fileobject, fieldnames) method. Use the resulting writer object’s writer.writeheader() method without argument to write the header. This writes the list of column names passed as fieldnames, e.g., the dictionary keys obtained via dict.keys(). After writing the header, you can then call the … Read more