get value by key dictionary python code example

Example 1: python dictionary get default

dictionary = {"message": "Hello, World!"}

data = dictionary.get("message", "")

print(data)  # Hello, World!

Example 2: python get dictionary keys

# To get all the keys of a dictionary use 'keys()'
newdict = {1:0, 2:0, 3:0}
newdict.keys()
# Output:
# dict_keys([1, 2, 3])

Example 3: python get value from dictionary

dict = {'color': 'blue', 'shape': 'square', 'perimeter':20}
dict.get('shape') #returns square

#You can also set a return value in case key doesn't exist (default is None)
dict.get('volume', 'The key was not found') #returns 'The key was not found'

Example 4: dict get default

dictionary.get("bogus", default_value)

Example 5: get() python

# The get() method on dicts
# and its "default" argument

name_for_userid = {
    382: "Alice",
    590: "Bob",
    951: "Dilbert",
}

def greeting(userid):
    return "Hi %s!" % name_for_userid.get(userid, "there")

>>> greeting(382)
"Hi Alice!"

>>> greeting(333333)
"Hi there!"

'''When "get()" is called it checks if the given key exists in the dict.

If it does exist, the value for that key is returned.

If it does not exist then the value of the default argument is returned instead.
'''
# transferred by @ebdeuslave
# From Dan Bader - realpython.com

Example 6: python dictionary access value by key

# Create a list of dictionary
datadict = [{'Name': 'John', 'Age': 38, 'City': 'Boston'},
 {'Name': 'Sara', 'Age': 47, 'City': 'Charlotte'},
 {'Name': 'Peter', 'Age': 63, 'City': 'London'},
 {'Name': 'Cecilia', 'Age': 28, 'City': 'Memphis'}]

# Build a function to access to list of dictionary
def getDictVal(listofdic, name, retrieve):
    for item in listofdic:
        if item.get('Name')==name:
            return item.get(retrieve)
          
 # Use the 'getDictVal' to read the data item
getDictVal(datadict, 'Sara', 'City') # Return 'Charlotte'

# -------------------
# to convert a dataframe to data dictionary
df = pd.DataFrame({'Name': ['John', 'Sara','Peter','Cecilia'],
                   'Age': [38, 47,63,28],
                  'City':['Boston', 'Charlotte','London','Memphis']})

datadict = df.to_dict('records')