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Tyler Hays
Tyler Hays

Reputation: 595

Pandas Dataframe from dict with empty list value

I am trying to read in a dictionary with two keys, the first with a string value and the second with a list of string values. The value containing a list can be (and often is) empty. For example:

{'number': '50', 'box': []}

However, when I try to use DataFrame.from_dict, it gives me an empty DataFrame. I notice that if the 'box' list has multiple elements, DataFrame.from_dict will give me a DataFrame with multiple rows, one for each value in the box list. This appears to be a sort of crossproduct behavior. Is there a way for me to suppress this behavior so that I can generate a DataFrame from the above example with one row, where the column "number" has value '50' and column "box" has value []?

I am using Pandas 0.16.2 and Python 2.7.10 via Anaconda 2.3.0 (64-bit Windows).

Upvotes: 3

Views: 6820

Answers (2)

YS-L
YS-L

Reputation: 14738

If you want to make a DataFrame with a single row, you can provide a list with a single dictionary:

df = pd.DataFrame([{'number': '50', 'box': []}])

The from_dict function expects a dict-of-lists, where the keys represent the columns and each value is a list (since DataFrame typically has more than one row) representing the values at each row. The following produces equivalent result using from_dict:

df = pd.DataFrame.from_dict({'number': ['50'], 'box': [[]]})

Upvotes: 3

dagrha
dagrha

Reputation: 2569

The documentation page doesn't show many options for this method. Instead of an empty list you could pass it [np.NaN]:

df = pd.DataFrame.from_dict({'number': '50', 'box': [np.NaN]})

which will return a dataframe with one row.

Upvotes: 0

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