In this article we will discuss how to create a list of all keys in a dictionary.
Suppose we have a dictionary of string and integers i.e.
# Dictionary of string and int wordFreqDic = { "Hello": 56, "at" : 23 , "test" : 43, "this" : 78, "here" : 18, "city" : 2, }
Now how to get all the keys from above dictionary in a list i.e.
['city', 'test', 'at', 'Hello', 'this', 'here']
Creating a list of all keys in dictionary using dict.keys()
In python, dictionary class provides a member function i.e.
dict.keys()
It returns a view object or iterator to the list of all keys in dictionary. We can use this object for iteration or creating new list. Let’s use that to get the list of all keys in the above dictionary.
# Create a new list from the view object returned by keys() dictkeys = list (wordFreqDic.keys())
dictkeys content will be,
['city', 'test', 'at', 'Hello', 'this', 'here']
Creating a filtered list of dictionary keys using List Comprehension
Suppose from above mentioned dictionary, we want a list of keys that start with character ‘t’ only i.e.
['test', 'this']
let’s do that using for loop i.e.
dictkeys = list() # Creating a list of keys that start with 't' for x in wordFreqDic : if x.startswith('t') : dictkeys.append(x)
dictkeys content will be,
['test', 'this']
But that’s not pythonic. Let’s do that using list comprehension,
# Creating a list of keys that start with 't' dictkeys = [x for x in wordFreqDic if x.startswith('t')]
dictkeys content will be,
['test', 'this']
Python Dictionary Tutorial - Series:
- What is a Dictionary in Python & why do we need it?
- Creating Dictionaries in Python
- Iterating over dictionaries
- Check if a key exists in dictionary
- Check if a value exists in dictionary
- Get all the keys in Dictionary
- Get all the Values in a Dictionary
- Remove a key from Dictionary
- Add key/value pairs in Dictionary
- Find keys by value in Dictionary
- Filter a dictionary by conditions
- Print dictionary line by line
- Convert a list to dictionary
- Sort a Dictionary by key
- Sort a dictionary by value in descending or ascending order
- Dictionary: Shallow vs Deep Copy
- Remove keys while Iterating
- Get all keys with maximum value
- Merge two or more dictionaries in python
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Complete example is as follows,
def main(): # Dictionary of string and int wordFreqDic = { "Hello": 56, "at" : 23 , "test" : 43, "this" : 78, "here" : 18, "city" : 2, } print("Dictionary : ", wordFreqDic) ''' Creating a list of keys in dictionary ''' # Create a new list from the view object returned by keys() dictkeys = list (wordFreqDic.keys()) print("List of keys in Dictionary : ", dictkeys) ''' Creating a filtered list of keys in dictionary using for loop ''' dictkeys = list() # Creating a list of keys that start with 't' for x in wordFreqDic : if x.startswith('t') : dictkeys.append(x) print("List of keys in Dictionary that start with 't' : " , dictkeys) ''' Creating a filtered list of keys in dictionary using List comprehension ''' # Creating a list of keys that start with 't' dictkeys = [x for x in wordFreqDic if x.startswith('t')] print("List of keys in Dictionary that start with 't' : " , dictkeys) if __name__ == '__main__': main()
Output:
Dictionary : {'city': 2, 'test': 43, 'at': 23, 'Hello': 56, 'this': 78, 'here': 18} List of keys in Dictionary : ['city', 'test', 'at', 'Hello', 'this', 'here'] List of keys in Dictionary that start with 't' : ['test', 'this'] List of keys in Dictionary that start with 't' : ['test', 'this']
Pandas Tutorials -Learn Data Analysis with Python
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Pandas Tutorial Part #1 - Introduction to Data Analysis with Python
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Pandas Tutorial Part #2 - Basics of Pandas Series
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Pandas Tutorial Part #3 - Get & Set Series values
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Pandas Tutorial Part #4 - Attributes & methods of Pandas Series
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Pandas Tutorial Part #5 - Add or Remove Pandas Series elements
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Pandas Tutorial Part #6 - Introduction to DataFrame
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Pandas Tutorial Part #7 - DataFrame.loc[] - Select Rows / Columns by Indexing
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Pandas Tutorial Part #8 - DataFrame.iloc[] - Select Rows / Columns by Label Names
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Pandas Tutorial Part #9 - Filter DataFrame Rows
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Pandas Tutorial Part #10 - Add/Remove DataFrame Rows & Columns
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Pandas Tutorial Part #11 - DataFrame attributes & methods
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Pandas Tutorial Part #12 - Handling Missing Data or NaN values
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Pandas Tutorial Part #13 - Iterate over Rows & Columns of DataFrame
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Pandas Tutorial Part #14 - Sorting DataFrame by Rows or Columns
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Pandas Tutorial Part #15 - Merging or Concatenating DataFrames
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Pandas Tutorial Part #16 - DataFrame GroupBy explained with examples
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