df = pd.DataFrame({'Name': ['John', 'Sara','Peter','Cecilia'],
'Age': [38, 47,63,28],
'City':['Boston', 'Charlotte','London','Memphis']})
datadict = df.to_dict('records')# Python code demonstrate how to create
# Pandas DataFrame by lists of dicts.
import pandas as pd
# Initialise data to lists.
data = [{'Geeks': 'dataframe', 'For': 'using', 'geeks': 'list'},
{'Geeks':10, 'For': 20, 'geeks': 30}]
# Creates DataFrame.
df = pd.DataFrame(data)
# Print the data
df# Supposing d is your list of dicts, simply
df = pd.DataFrame(d)
# Note: this does not work with nested datadf = pd.DataFrame(d) #here d is list of dict In [20]: timeit df.T.to_dict().values()
1000 loops, best of 3: 395 µs per loop
In [21]: timeit df.to_dict('records')
10000 loops, best of 3: 53 µs per loopIn [2]: df.to_dict('records')
Out[2]:
[{'customer': 1L, 'item1': 'apple', 'item2': 'milk', 'item3': 'tomato'},
{'customer': 2L, 'item1': 'water', 'item2': 'orange', 'item3': 'potato'},
{'customer': 3L, 'item1': 'juice', 'item2': 'mango', 'item3': 'chips'}]