Pandas– ValueError: If using all scalar values, you must pass an index

For Python users, we all know that it is very convenient to create a data frame from a dictionary. For example:

df = pd.DataFrame({‘Key’:[‘a’,’b’,’c’,’d’], ‘Value’:[1,2,3,4]})

It works beautifully when the values is a list/dict with multiple columns. However, you may encounter into syntax errors “ValueError: If using all scalar values, you must pass an index” when you try to convert the following dictionary to a data frame.

dict_test = {

‘bacon’:’pig’,

‘pulled pork’:’pig’,

‘pastrami’: ‘cow’,

‘honey ham’:’pip’,

‘nova lox’: ‘salmon’

}

df = pd.DataFrame.from_dict(dict_test)

Why is that?

While pandas create data frame from a dictionary, it is expecting its value to be a list or dict. If you give it a scalar, you’ll also need to supply index. In this example, the values are ‘pig’ instead of [‘pig’].

How to fix it:

1. Change the data to:

dict_test = {

‘bacon’:[‘pig’],

‘pulled pork’:[‘pig’],

‘pastrami’: [‘cow’],

‘honey ham’:[‘pip’],

‘nova lox’: [‘salmon’]

}

2. Get the list items from the dictionary and add ‘list’ for Python 3.x.

pd.DataFrame.from_dict(list(dict_test.items()), columns = [‘food’,’animal’])

3. Specify the orientation with ‘index’.

pd.DataFrame.from_dict(dict_test, orient = ‘index’)

4. Pass the Series constructor instead:

s = pd.Series(dict_test, name = ‘animal’)

s.index.name = ‘Food’

df = pd.DataFrame(s)