![]() ![]() Step – 6 : Finally we will print the result.Python Dictionaries Access Items Change Items Add Items Remove Items Loop Dictionaries Copy Dictionaries Nested Dictionaries Dictionary Methods Dictionary Exercise Python If.Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Polymorphism Python Scope Python Modules Python Dates Python Math Python JSON Python RegEx Python PIP Python Try. Step – 5 : Here we will convert the result we got in the last step into a list of dictionaries using the to_dict() method and we need to pass another argument inside it which is “records”, now if we don’t pass any argument then it will return a dictionary of dictionaries, but the “record” parameter is used to tell it convert it to list of dictionaries. Step – 4 : Then we will use the groupby method by passing the “school_id” as a parameter to group together all the roll_no for a single school_id, we will also use the list() function on roll_no column for each of the groups by using the apply() method.įinally we will use the reset_index() method to convert the grouped DataFrame into a normal DataFrame with school_id and the roll_id keys as columns. Step – 3 : Then using another variable we will use the concat() method of Pandas to concatenate those two lists of dictionaries Step – 2 : Then we will need to use two more variables to convert each of those lists into DataFrames. Step – 1 : Firstly we will require two variables to store two lists of dictionaries. Using the inbuilt merge() and to_dict() methods of Pandas library we can merge a list of dictionaries into 1 in Python by first converting them into DataFrames. Merging two list of dictionaries Using Pandas library Space complexity: O(n), where n is the total number of entries in the input lists.
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