How to convert floats to strings with Python and Pandas?

In this tutorial we’ll learn about different ways that we can use to convert one or multiple float numbers to string objects in Python.

Convert a floating number to string

In order to cast a single float number into a string you can use the Python str function:

# strat by defining a float number
fl_val = 97.1111

# cast float to string
str_val = str(fl_val)

print ('The workshop attendance rate was ' +str_val +'%.')

This will return:

The workshop attendance rate was 97.1111%.

Float to string with rounding

If we would like to get rid of the decimals, we can round the float first:

fl_val = 97.1111

# round the float number
str_val = str(round(fl_val))

print ('The workshop attendance rate was ' +str_val +'%.')

And here is our result:

The workshop attendance rate was 97%.

Rounding with 2 decimal precision and converting to string

We can round up values with specific precision using the round() Python function.

fl_val = 97.1111
str_val = str(round(fl_val,2))
print ('The workshop attendance rate was ' +str_val +'%.')

The result will be:

The workshop attendance rate was 97.11%.

Convert a list of floats to strings

The methods outlined below need to be slightly adjusted to handle a list object populated with floats:

#list of floating numbers

fl_lst = [98.2, 97.4, 95.111]

# use a list comprehension to round and cast to string
str_lst = [str(round(x,1)) for x in fl_lst]

#print the list of strings

And here is the result:

['98.2', '97.4', '95.1']

Convert float Pandas Series to strings

You can also perform similar manipulations on a Pandas Series (DataFrame column).

# import pandas
import pandas as pd

fl_lst = [98.2, 97.4, 95.111]

# define list of floats
fl_s = pd.Series(fl_lst)

#export to string

Numpy array of floats to strings

# import the numpy library
import numpy as np

fl_lst = [98.2, 97.4, 95.111]

# define numpy array from list
fl_arr = np.array(fl_lst)

#convert float array to strings

Here is the resulting array of strings:

array(['98.2', '97.4', '95.111'], dtype='<U32')

Additional learning