Search results
DataFrame.to_dict() converts DataFrame to dictionary. Example >>> df = pd.DataFrame( {'col1': [1, 2], 'col2': [0.5, 0.75]}, index=['a', 'b']) >>> df col1 col2 a 1 0.1 b 2 0.2 >>> df.to_dict() {'col1': {'a': 1, 'b': 2}, 'col2': {'a': 0.5, 'b': 0.75}}
You can use df.to_dict () in order to convert the DataFrame to a dictionary. Here is the complete code to perform the conversion: import pandas as pd. data = { "Product": ["Laptop", "Printer", "Monitor", "Tablet"], "Price": [1200, 100, 300, 150], } df = pd.DataFrame(data) my_dictionary = df.to_dict() print (my_dictionary)
mydict = dict(zip(zip(df['A'],df['B']), df['C'])) Using pandas to_dict() also works: mydict = df.set_index(['A','B']).to_dict(orient='dict')['C'] (none of the columns A or B are used as an index before executing the line creating the dictionary)
In this tutorial, we will see how to change a DataFrame into a dictionary in Pandas. Table of Contents. Using to_dict () method. Dictionary with Column Values. Using set_index () for Nested Dictionary. Using iterrows () Method. Conclusion. 1. Using to_dict () method.
30 wrz 2022 · Convert a Pandas DataFrame to a Dictionary. By default, the Pandas DataFrame .to_dict () method will return a dictionary where the keys are the columns and the values are the index:record matches. This process is more informative when your indices are meaningful, rather than arbitrary numbers.
pandas.DataFrame.to_dict# DataFrame. to_dict (orient='dict', *, into=<class 'dict'>, index=True) [source] # Convert the DataFrame to a dictionary. The type of the key-value pairs can be customized with the parameters (see below). Parameters: orient str {‘dict’, ‘list’, ‘series’, ‘split’, ‘tight’, ‘records’, ‘index’}
18 lut 2024 · Method 1: Using to_dict () with ‘dict’ orientation. In this method, the to_dict () method of a pandas DataFrame is used with the default ‘dict’ orientation. This converts the DataFrame into a dictionary where each column becomes a key and the corresponding values are lists of column data.
