# Can only concatenate str (not "numpy.int64") to str Wed Apr 20 20222 min read ## Can only concatenate str (not "numpy.int64") to str#

The Python "TypeError: Can only concatenate str (not "numpy.int64") to str" occurs when we try to concatenate a string and a numpy int. To solve the error, convert the numpy int to a string, e.g. `str(my_numpy_int)` to concatenate the strings. Here is an example of how the error occurs.

main.py
```Copied!```import numpy as np

str_1 = 'it costs: '

num_1 = np.power(10, 3, dtype=np.int64)

# ⛔️ TypeError: can only concatenate str (not "numpy.int64") to str
result = str_1 + num_1
``````
We tried to use the addition (+) operator to concatenate a string and an integer which caused the error.

The values on the left and right-hand sides need to be of compatible types.

One way to solve the error is to convert the numpy int to a string.

main.py
```Copied!```import numpy as np

str_1 = 'it costs: '

num_1 = np.power(10, 3, dtype=np.int64)

# 👇️ convert to str
result = str_1 + str(num_1)

print(result)  # 👉️ 'it costs: 1000'
``````

We passed the numpy integer to the `str()` class and converted it to a string before concatenating the two strings.

If you have a number that is wrapped in a string and an integer, you need to convert the string to an integer (or float) to add the two numbers.

main.py
```Copied!```import numpy as np

str_1 = '500'

num_1 = np.power(10, 3, dtype=np.int64)

result = int(str_1) + num_1
print(result)  # 👉️ 1500
``````

We passed the string to the `int()` class to convert it to an integer. Note that you can also use the `float()` class if you need to convert a string to a floating-point number.

IMPORTANT: if you use the `input()` built-in function, all of the values the user enters get converted to strings (even numeric values).

An alternative to concatenating strings with the addition (+) operator is to use a formatted string literal.

main.py
```Copied!```import numpy as np

str_1 = 'it costs'
num_1 = np.power(10, 3, dtype=np.int64)

result = f'{str_1} {num_1} usd'

print(result)  # 👉️ 'it costs 1000 usd'
``````
Formatted string literals (f-strings) let us include expressions inside of a string by prefixing the string with `f`.

Make sure to wrap expressions in curly braces - `{expression}`.

If you aren't sure what type a variable stores, use the built-in `type()` class.

main.py
```Copied!```import numpy as np

str_1 = 'it costs'
print(type(str_1))  # 👉️ <class 'str'>
print(isinstance(str_1, str))  # 👉️ True

num_1 = np.power(10, 3, dtype=np.int64)
print(type(num_1))  # 👉️ <class 'numpy.int64'>
print(isinstance(num_1, np.int64))  # 👉️ True
``````

The type class returns the type of an object.

The isinstance function returns `True` if the passed in object is an instance or a subclass of the passed in class.

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