Category : merge

I am joining two data frames that have the same columns. I wanted to update the first dataframe. However, the my code creates additional columns but it is not updating. My code: left = pd.DataFrame({"key": ["K0", "K1", "K2", "K3"], "A": ["NaN", "NaN", "NaN", "NaN"], "B": ["B0", "B1", "B2", "B3"],}) right = pd.DataFrame({"key": ["K1", "K2", "K3"], ..

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Dict 1 : [{"result1":[{"1":"11"},{"11":"111"}]},{"result2":[{"2":"22"},{"22":"222"}]}] Dict 2: [{"result1":[{"one":"eleven"},{"11":"111"}]},{"result2":[{"two":"twentytwo"},{"22":"222"}]}] I want to merge them based on keys result1 and result 2 and preserve the same format. Expected Output [{"result1":[{"1":"11"},{"one":"eleven"},{"11":"111"}]},{"result2":[{"2":"22"},{"two":"twentytwo"},{"22":"222"}]}] Source: Python..

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I’m trying to get a simple Python code to merge a list of dictionaries into a condensed list as I have lots of duplicates atm. From this: [ { "module": "RECEIPT BISCUITS", "product_range": "ULKER BISCUITS", "receipt_category": "BISCUITS" }, { "module": "RECEIPT BISCUITS", "product_range": "ULKER", "receipt_category": "BISCUITS" }, { "module": "RECEIPT BISCUITS", "product_range": "ULKER BISCUITS GOLD", ..

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The data I’m analyzing has a structure similar to this one: df = pd.DataFrame( { "group": ["group1", "group1", "group2", "group2", "group2", "group3", "group3", "group3", "group4", "group4", "group4", "group4", "group5", "group5"], "letter": ["B1", "B2", "B1", "B2", "B3", "B1", "B2", "B4", "B2", "B1", "B3", "B4", "B3", "B4"] }) I want to get the possible combination of elements ..

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