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I'm new to Python and could use some help. I have a function that takes a pandas DataFrame and returns an ordered dictionary to create a YAML file, and another function that takes the created ordered dictionary and performs a YAML dump. The function works for single dictionaries, but I want to add an additional function that can output multiple input dictionaries onto one YAML file.

Take these two DataFrames for example, and convert them into two ordered dictionaries:
df1:
      Name        Occupation  Years  JobSatisfaction
0     Lucy Black  Teacher     10     Yes
1     John Doe    Gardener    3      Yes

df2:
      Name        Age  Salary  Company Name
0     Lucy Black  31   $38000  LAUSD
1     John Doe    23   $17000  Beautiful Lawn


Now, how would you read both ordered dictionaries at once and get the YAML output to look like this:
Python
# In this case, the key_index='Name'for both df1 and df2:

-df1:
  -Lucy Black:
      -Occupation:Teacher
      -Years:10
      -JobSatisfaction:Yes
  -John Doe:
      -Occupation:Gardener
      -Years:3
      -JobSatisfaction:Yes
-df2:
  -Lucy Black:
      -Age: 31
      -Salary: $38000
      -Company Name: LAUSD
  -John Doe:
      -Age: 23
      -Salary: $17000
      -Company Name: Beautiful Lawn


Here is some skeleton code with my preferred code format:
Python
def yaml_output(arguments):
"""
considerations/notes/checks:
        - we want the output yaml to have one outermost dictionary per input 
          excel sheet (so in our case, this will be two total: df1, df2)
        - confirm the first two entries for each dictionary match the example 
          yaml file contained in this directory
"""    
    function parameters
    return() 


What I have tried:

And this is what my code looks like so far:
Python
def create_dict(df, key_index='uniqueID'):
    """
    Function create_dict to take input pandas df and return dictionary which will 
    then be used to create final YAML file

    args:
        df: pandas 2-dim labeled data structure
        key_index: the column that we want set as the index
    
    input: pandas df
    returns: dictionary

    """
    # Get the unordered dictionary
    unordered_dict = df.set_index(key_index).T.to_dict()
    
    # Order the dictionary
    ordered_dict = OrderedDict((k,unordered_dict.get(k)) for k in df[key_index])
    
    return ordered_dict
    

def dump_ordered(dictionary):
    """
    Serialize the ordered dictionary into a YAML stream 
    
    args:
        dictionary: ordered collection of data values that were 
        converted from pandas dataframes
    
    input: Ordered dictionary
    return: ordered yaml 
    """
    yaml.add_representer(OrderedDict, lambda dumper, 
                         data:dumper.represent_mapping('tag:yaml.org,2002:map',     
                         data.items()))

    return yaml.dump(dictionary)

Ultimately, I want to be able to pass the newly created function a variable number of dictionaries with each dictionary's name (could be a list of tuples?), so all dictionaries become one output YAML file. Let me know if you need additional clarification. Thank you!
Posted

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