DataFrame constructor not properly called

Question

I am trying to create a dataframe with Python, which raise the Error in the qustion title

  # pre processing to get G-Test score
    def G_test(tokens, types):
        tokens_cnt = tokens.value_counts().astype(float)
        types_cnt = types.value_counts().astype(float)
        total_cnt = float(sum(tokens_cnt))
    
        # calculate each token counts
        token_cnt_table = collections.defaultdict(lambda : collections.Counter())
        for _tokens, _types in zip(tokens.values, types.values):
            token_cnt_table[_tokens][_types] += 1
    

 tc_dataframe = pd.DataFrame(token_cnt_table.values(), index=token_cnt_table.keys())

        tc_dataframe.fillna(0, inplace=True)
        for column in tc_dataframe.columns.tolist():
            tc_dataframe[column+'_exp'] = (tokens_cnt / total_cnt) * types_cnt[column]
            c_dataframe[column+'_GTest'] = [G_test_score(tkn_count, exp) for tkn_count, exp in zip(tc_dataframe[column], tc_dataframe[column+'_exp'])]
            return tc_dataframe

Solution 1

The pd.DataFrame constructor does not accept a dictionary view as data. You can convert to list instead. Here's a minimal example:

d = {'a': 1, 'b': 2, 'c': 3}

df = pd.DataFrame(d.values(), index=d.keys())
# PandasError: DataFrame constructor not properly called!

df = pd.DataFrame(list(d.values()), index=d.keys())
# Works!

The docs do suggest this:

data : numpy ndarray (structured or homogeneous), dict, or DataFrame

Equivalently, you can use pd.DataFrame.from_dict, which accepts a dictionary directly:

df = pd.DataFrame.from_dict(d, orient='index')

Solution 2

This worked for me

df = pd.Dataframe([data])

Comments

[Mak Haj]

tc_dataframe = pd.DataFrame(token_cnt_table.values(), index=token_cnt_table.keys()) the error always in this line

[FHTMitchell]

What is the full error traceback?