Interview Pandas Python

Formatting strings and numbers in python

6 ways in which you can format your string/numerical output in python

About this article

Most of the time, a sample print() statement might lead to messy code. And sometimes you do not need a logger to handle the job. Python offers different output options to deal with your string outputs. Here are a few Formatting strings.

1. Using %s in statements

print(“Some text %s some text %s some text “ %(str1,str2))

str1 and str2 takes the place of %s and %s in that order

You can even do mathematical operations in string outputs .

print a character many times

2. Formatting using f-prefix

We can write the same code using the f-string method .

It overcomes the limitation that %s has — you cannot specify an order (‘easily’) . So when you are using {variable_name} you embed these in the desired parts of your statement and naturally overcome the ‘order-problem’

3. Aligning the output neatly using f-prefix

You can use the :>:< or :^ option in the f-format to left align, right align or center align the text that you want to format.

without formatting

After formatting the alignment of output text …

after formatting to right align

4. Using the format keyword

We can use the fortmat() string function in python to output the desired text in the order we want.

using the format() function in python

Formatting numbers

Now extending the formatting using f keyword ( look at the piece above ) , lets try to use that in numbers, particularly involving decimals ( float )

1.Restricting the number of digits after the decimal point

eg: if i want to restrict the value of pi ( to the 2nd or 3rd decimal )

Numerical outputs

Normally, we would get this as a result

The normal expected output

Now by formatting the number, we can restrict the number of decimals to 2 digits ….

restricting to 2 decimal points

or to 3 digits …

restricting to 3 decimal points

2. Formatting the output in pandas data-frames

To take it a little further, if you want to display the numbers in a particular format in your dataframe, when using pandas you can use the pd.options.display to show the way you want it. Here is an example of how numbers are displayed , before and after you enable the options.display settings.

Lets take an example —

We are reading a file test.csv and displaying the contents. We see that the length column has 6 decimal places displayed.

Normal display with 6 decimal points displayed against the length column

If we are interested in only displaying 2 decimal places, we can change it using the pd.options.display attribute. Below is the output of the dataframe after the formatting is applied.

output after setting the format of the float data type to 2 decimal places

Note : Here on , for all the pandas displays ( even for other data-frames), only 2 decimal points will be displayed. If you want to set it back to 4 or 5 decimal points , you will have to set the format back to which ever format you want. Till then it will continue to display only 2 decimal points.

3. Formatting the output in numpy

Numpy has settings to change the decimal point precision to a desired one.


Lets see the output as an extension to the previous example from pandas .

Changing the decimal point precision in numpy

Python related blogs Visit Us Geekycodes . This Notebook has been provided on Medium by Lars Nielsen

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