J.1 Line Breaks in Code

Writing analysis code does get very wide at times. An additional constraint in the book is that the code needs to be even more narrow compared to the PEP8 rules.

There are two ways you can break up wide lines of code.

1. Using the at the end of a line to tell Python that the code continues on the next line

2. Wrapping your entire statement around a pair of round parentheses ( )

Let’s use the example from Section 4.3.

Click here to view code image

import pandas as pd
weather = pd.read_csv('data/weather.csv')

The first step in tidying up the data set was to call the .melt() method.

Click here to view code image

# this code is wide and will run off the page
weather_melt = weather.melt(id_vars=["id", "year", "month", "element"],
var_name="day", value_name="temp")

This ends up being a wide line of code. So we can put in line breaks between the round parenthesis of the .melt() method call.

Click here to view code image

# previous line of code can be rewritten as
weather_melt = weather.melt(
  id_vars=["id", "year", "month", "element"],
  var_name="day",
  value_name="temp",
)

In Pandas, many of the methods can be chained together (Appendix U). A common practice is to put each method call on its own line. This way if your eyes look down a straight line, you can get a rough overview of all the steps your data is going through. However, just putting arbitrary line breaks outside of a function call does not work.

Click here to view code image

# this will error, putting line break before the .melt
# previous line of code can be rewritten as
weather_melt = weather
  .melt(
    id_vars=["id", "year", "month", "element"],
    var_name="day",
    value_name="temp")

IndentationError: unexpected indent (3804754158.py, line 4)

We can solve this by using one of the techniques listed above

Click here to view code image

# use a  at the end of the line
weather_melt = weather 
  .melt(
    id_vars=["id", "year", "month", "element"],
    var_name="day",
    value_name="temp")

# wrap the entire statement around ( )
weather_melt = (weather
  .melt(
    id_vars=["id", "year", "month", "element"],
    var_name="day",
    value_name="temp")
)

The ( ) method is the style you will see more often reading Pandas code.