How to create a Dataframe from a dict with the keys as header and the values as rows?-CodePudding

This is my dict with emotions and their probabilities:

{'angry': 0.08,
'disgust': 0.0,
'fear': 0.16,
'happy': 0.05,
'sad': 0.02,
'surprise': 0.68,
'neutral': 0.02}

I want the emotions e.g, 'angry' as header, and the probabilities as rows. Does someone know how to make a df of it?

CodePudding user response：

You can use the

Also, as correctly posted in other answers, if you want to adjust your dictionary into the correct format:

data = {k: [v] for k, v in data.items()}

Pandas DataFrame documentation

CodePudding user response：

d = {
 'angry': 0.08,
 'disgust': 0.0,
 'fear': 0.16,
 'happy': 0.05,
 'sad': 0.02,
 'surprise': 0.68,
 'neutral': 0.02
}
pd.DataFrame(data=[d.values()], columns=d.keys())

Result:

   angry  disgust  fear  happy   sad  surprise  neutral
0   0.08      0.0  0.16   0.05  0.02      0.68     0.02

CodePudding user response：

First you need to pass for each key in your dict a list of values:

{'angry': [0.08],'disgust': [0.0],'fear': [0.16],'happy': [0.05],'sad': [0.02],'surprise': [0.68],'neutral': [0.02]}

Then you can simply use pandas like this:

import pandas as pd
dict = {'angry': [0.08],'disgust': [0.0],'fear': [0.16],'happy': [0.05],'sad': [0.02],'surprise': [0.68],'neutral': [0.02]}
df = pd.DataFrame(dict)
print(df)
>>    angry  disgust  fear  happy   sad  surprise  neutral
0      0.08   0.0      0.16 0.05    0.0   0.68      0.02

CodePudding user response：

You can use a Series and convert to DataFrame:

pd.Series(d).to_frame().T

or use pandas.DataFrame.from_dict:

pd.DataFrame.from_dict(d, orient='index').T

output:

   angry  disgust  fear  happy   sad  surprise  neutral
0   0.08      0.0  0.16   0.05  0.02      0.68     0.02

input:

d = {'angry': 0.08,
    'disgust': 0.0,
    'fear': 0.16,
    'happy': 0.05,
    'sad': 0.02,
    'surprise': 0.68,
    'neutral': 0.02}