Python | Pythonic way of constructing a list of dictionaries by row

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List of dictionaries - by row

In Python, you can create a list of dictionaries where each dictionary represents a row of data. This is a common way to represent data when working with Pandas dataframes, as each dictionary represents a single row of data in the dataframe.

Here's an example of how to create a list of dictionaries by row:

# create a list of dictionaries by row

data = [

{'name': 'John', 'age': 30, 'gender': 'M'},

{'name': 'Jane', 'age': 25, 'gender': 'F'},

{'name': 'Mike', 'age': 35, 'gender': 'M'},

{'name': 'Susan', 'age': 40, 'gender': 'F'}

]

# loop through the list of dictionaries and print each row of data

for row in data:

print(row)

This will output each row of data as a dictionary:

{'name': 'John', 'age': 30, 'gender': 'M'}

{'name': 'Jane', 'age': 25, 'gender': 'F'}

{'name': 'Mike', 'age': 35, 'gender': 'M'}

{'name': 'Susan', 'age': 40, 'gender': 'F'}

In this example, the data list contains four dictionaries, each representing a single row of data with the keys name, age, and gender.

You can also add or modify data in a list of dictionaries by row using the dictionary keys:

# add a new row of data to the list of dictionaries

data.append({'name': 'Tom', 'age': 45, 'gender': 'M'})

# modify the age of an existing row of data

data[1]['age'] = 30

# loop through the updated list of dictionaries and print each row of data

for row in data:

print(row)

This will output the updated list of dictionaries:

{'name': 'John', 'age': 30, 'gender': 'M'}

{'name': 'Jane', 'age': 30, 'gender': 'F'}

{'name': 'Mike', 'age': 35, 'gender': 'M'}

{'name': 'Susan', 'age': 40, 'gender': 'F'}

{'name': 'Tom', 'age': 45, 'gender': 'M'}

In this example, we added a new row of data to the data list using the append() method, and modified the age of an existing row of data by accessing it with its index and key.