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I have a dataframe as below:

+----+----------------+-------------+----------------+-----------+
|    |   attribute_one|   value_one |  attribute_two | value_two |
|----+----------------+-------------+----------------+-----------|
|  0 |      male      |    10       |  female        |    15     |
|  1 |     34-45      |    17       |  55-64         |     8     |
|  2 |     graduate   |    32       |  high school   |     5     |
...

I want to convert it into dictionary that gives this output:

{'male': '10', 
 '34-45':'17',
 'graduate':'32'
 'female':'15',
 '55-64': '8', 
 'high school': '5'
 }

How do I do that? I only want attribute columns as keys and their value columns as values.

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  • $\begingroup$ Do let me know if you are satisfied with the answer? If not I will try my best possible way to edit it. Please consider accepting the answer if it answers your question. $\endgroup$ Commented Jun 16, 2021 at 12:17
  • 1
    $\begingroup$ Thank you, that worked! $\endgroup$ Commented Jun 16, 2021 at 16:09

2 Answers 2

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Explanation is mentioned in comments

# Created some data like yours
data = {
    'attribute_one':['male','34-45','graduate'],
    'value_one':[10,17,32],
    'attribute_two':['female','55-64','high school'],
    'value_two':[15,8,5]
    }

# Pandas for handling dataframes
import pandas as pd

# Created a dataframe from the given data
df = pd.DataFrame(data)

# Sliced the columns of interests
df1 = df.iloc[:,0:2] # all values of first two columns
df2 = df.iloc[:,2:4] # all values of last two columns

# Final dictionary for the output
your_dict = {}

# Iterate through numpy values of dataframes
for i in df1.to_numpy():
  your_dict[i[0]] = i[1] # populate the dictionary with first dataframe
for i in df2.to_numpy():
  your_dict[i[0]] = i[1] # populate the dictionary with second dataframe

# Your dictionary is ready
print(your_dict)
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You may encounter that if an attribute has previously be assigned as a key it will overwrite the dictionary value if the attribute names are not unique.

Storing a list can mitigate this issue.

import pandas as pd

# convert to dict with list of values
def convert_to_dict(df):
    df_dict = {}    # empty dict
    
    for row in df.itertuples():    # itertuples for each row
        
        # make a new list for a new key
        if row.attribute_one not in df_dict:
            df_dict[row.attribute_one] = []
            
        df_dict[row.attribute_one].append(row.value_one)
        
        # make a new list for a new key
        if row.attribute_two not in df_dict:
            df_dict[row.attribute_two] = []
            
        # append value
        df_dict[row.attribute_two] = row.value_two
        
    return df_dict


# Original Data
data = {
    'attribute_one': ['male', '34-45', 'graduate'],
    'value_one': [10, 17, 32],
    'attribute_two': ['female', '55-64', 'high school'],
    'value_two': [15, 8, 5]
    }

# Dataframe
df_data = pd.DataFrame(data)

# Data in dictionary format
data = list_of_dicts(df_data)

print(data)
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