ValueError: Mixing dicts with non-Series may lead to ambiguous ordering - Pandas   

In this tutorial, we'll see how to solve a Pandas error – "ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.".

We get this error from the Pandas when we try to create DataFrame with mixed elements:

• dictionaries
• non-Series
• list
• etc

In short to solve this error use json_normalize():

from pandas import json_normalize
json_normalize(data)

Reproduce the error

First let's see an example with this error. Suppose we have data for the Game of Thrones movie - data is extracted from imdb by library - cinemagoer.

If you like to find how to extract and analyze IMDB with Python you can follow youtube channel - DataScientYst - we are planning video on this topic.

We would like to create DataFrame with this data like:

import pandas as pd

data = {'title': 'Game of Thrones',
 'year': 2011,
 'kind': 'tv series',
 'taglines': ['Winter is coming.',
  'Winter is here. (season 7)',
  'The Great War Is Here (Season 8)',
  'For the Throne.'],
 'number of votes': {10: 1210366,   9: 444762,  8: 192847,  7: 76850,  6: 30220,  
                     5: 18478,  4: 9341,   3: 7930,  2: 7145,  1: 65485},
 'arithmetic mean': 9.0,
 'median': 1}

pd.DataFrame(data)

we got error like:

ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.

the one mentioned in the title.

Solve the error - json_normalize

To solve this error we will use: json_normalize

from pandas import json_normalize
json_normalize(data)

Now we can create DataFrame from the input data without error. DataFrame below is transposed - for readability:

Solve the error - json

Alternatively we can read only the important information for us by:

import pandas as pd
df = pd.DataFrame(data["taglines"])

which give us:

or if we read json file we can use Python json library to load the file as:

import json

data = json.load(open('data.json'))

df = pd.DataFrame(data["taglines"])