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:

```
#Python3
# 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 was97%.

### 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 was97.11%.

### 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
print(str_lst)
```

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
fl_s.to_string(index=False)
```

### 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
fl_arr.astype(str)
```

Here is the resulting array of strings:

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