Dictionary to pandas dataframe in python-CodePudding

I have a dictionary:

{'1': -1.4, '8': -6.04, '6': 0.75}

I want to convert this to a dataframe that looks like:

     code  score 
      1     -1.4 
      8     -6.04
      6     0.75

CodePudding user response：

You can use pd.Dataframe(), as follows:

d = {'1': -1.4, '8': -6.04, '6': 0.75}
df = pd.DataFrame({'code': d.keys(), 'score': d.values()})

or use pd.Series .reset_index():

d = {'1': -1.4, '8': -6.04, '6': 0.75}
df = pd.Series(d).rename_axis(index='code').reset_index(name='score')

Result:

print(df)

  code  score
0    1  -1.40
1    8  -6.04
2    6   0.75

CodePudding user response：

Another way:

d = {'1': -1.4, '8': -6.04, '6': 0.75}
df = pd.DataFrame.from_dict(d, orient='index', columns=['score']) \
                 .rename_axis('code') \
                 .reset_index()

Output:

>>> df
  code  score
0    1  -1.40
1    8  -6.04
2    6   0.75

CodePudding user response：

The generic code to convert JSON to any number of columns dataframe

data={'1': -1.4, '8': -6.04, '6': 0.75}
df=pd.DataFrame([data]).T.reset_index() # create dataframe and transpose it
df.columns=['code', 'score'] # set the column names

Result:

  code  score
0    1  -1.40
1    8  -6.04
2    6   0.75