Example 1: pandas dataframe from dict
data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
pd.DataFrame.from_dict(data)
Example 2: pandas dataframe from dict
>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data)
col_1 col_2
0 3 a
1 2 b
2 1 c
3 0 d
Example 3: convert dict to dataframe
#Lazy way to convert json dict to df
pd.DataFrame.from_dict(data, orient='index').T
Example 4: python dictionary
#Creating dictionaries
dict1 = {'color': 'blue', 'shape': 'square', 'volume':40}
dict2 = {'color': 'red', 'edges': 4, 'perimeter':15}
#Creating new pairs and updating old ones
dict1['area'] = 25 #{'color': 'blue', 'shape': 'square', 'volume': 40, 'area': 25}
dict2['perimeter'] = 20 #{'color': 'red', 'edges': 4, 'perimeter': 20}
#Accessing values through keys
print(dict1['shape'])
#You can also use get, which doesn't cause an exception when the key is not found
dict1.get('false_key') #returns None
dict1.get('false_key', "key not found") #returns the custom message that you wrote
#Deleting pairs
dict1.pop('volume')
#Merging two dictionaries
dict1.update(dict2) #if a key exists in both, it takes the value of the second dict
dict1 #{'color': 'red', 'shape': 'square', 'area': 25, 'edges': 4, 'perimeter': 20}
#Getting only the values, keys or both (can be used in loops)
dict1.values() #dict_values(['red', 'square', 25, 4, 20])
dict1.keys() #dict_keys(['color', 'shape', 'area', 'edges', 'perimeter'])
dict1.items()
#dict_items([('color', 'red'), ('shape', 'square'), ('area', 25), ('edges', 4), ('perimeter', 20)])
Example 5: python 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 york
Example 6: dicts python
thisdict = {
"brand": "Ford",
"model": "Mustang",
"year": 1964
}
x = thisdict["model"]
print(x)
---------------------------------------------------------------------------
Mustang