pandas dataframe from dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)pandas dataframe from dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)convert a dictionary into dataframe python
import pandas as pd
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data, orient='index').Tpandas dataframe from dict
>>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data, orient='index')
0 1 2 3
row_1 3 2 1 0
row_2 a b c dpython how to create a pandas dataframe from a dictionary
# Basic syntax:
import pandas as pd
pandas_dataframe = pd.DataFrame(dictionary)
# Note, with this command, the keys become the column names
# Create dictionary:
import pandas as pd
student_data = {'name' : ['Jack', 'Riti', 'Aadi'], # Define dictionary
'age' : [34, 30, 16],
'city' : ['Sydney', 'Delhi', 'New york']}
# Example usage 1:
pandas_dataframe = pd.DataFrame(student_data)
print(pandas_dataframe)
name age city # Dictionary keys become column names
0 Jack 34 Sydney
1 Riti 30 Delhi
2 Aadi 16 New york
# Example usage 2:
# Only select listed dictionary keys to dataframe columns:
pandas_dataframe = pd.DataFrame(student_data, columns=['name', 'city'])
print(pandas_dataframe)
name city
0 Jack Sydney
1 Riti Delhi
2 Aadi New york
# Example usage 3:
# Make pandas dataframe with keys as rownames:
pandas_dataframe = pd.DataFrame.from_dict(student_data, orient='index')
print(pandas_dataframe)
0 1 2
name Jack Riti Aadi # Keys become rownames
age 34 30 16
city Sydney Delhi New yorkpandas dataframe from dict
>>> pd.DataFrame.from_dict(data, orient='index',
... columns=['A', 'B', 'C', 'D'])
A B C D
row_1 3 2 1 0
row_2 a b c dCopyright © 2021 Codeinu
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