How to create a Dataframe from multiple dictionaries-CodePudding

I have a little issue with my the data I have (multiple dictionaries) to process and create a Dataframe from them. At the moment I'm a beginner so I'm struggling to make this happen.

This what the data look like:

print(data)
0         {'john': True}
1         {'joe': True}
2         {'tom': True}
3         {'mark': False}
4         {'andrew': True}
                       ...                  
93        {'david': False}
94        {'luke': False}
95        {'vincent': True}
96        {'oliver': True}
97        {'matthew': True}
Length: 98, dtype: object

Basically what I want is this:

df = pd.DataFrame()
df['name'] = data[0].keys()
df['result'] = data[0].values()
print(df)

    name    result
0   john    True

So 1 dataframe with 2 columns - name and result.

How can I apply that procedure for all dictionaries in data and have 1 output in the same Dataframe? I was not able to replicate that action via lambda function, but maybe I was not doing it right.

Thanks in advance for all advices

CodePudding user response：

pd.DataFrame(data.apply(lambda x: list(x.items())[0]).values.tolist())

you can rename columns, using:

df.rename(columns={0: 'name', 1: 'result'}, inplace=True)

CodePudding user response：

You can save the keys and the values of your dictionaries in lists, and then create your DataFrame from them. There is probably a better way to do it but it works!

import pandas as pd

data = [{'john': True}, {'joe': True}, {'tom': True}, {'mark': False}, {'andrew': True}, {'david': False}, {'luke': False}]

names = []
results = []

for dict1 in data:
    name = list(dict1.keys())[0]
    result = list(dict1.values())[0]
    names.append(name)
    results.append(result)
    
df = pd.DataFrame(zip(names, results), columns=["name", "result"])

print(df)

Output

     name  result
0    john    True
1     joe    True
2     tom    True
3    mark   False
4  andrew    True
5   david   False
6    luke   False