Return multiple columns from pandas apply()

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I have a pandas DataFrame, df_test. It contains a column "size" which represents size in bytes. I"ve calculated KB, MB, and GB using the following code:

df_test = pd.DataFrame([
    {"dir": "/Users/uname1", "size": 994933},
    {"dir": "/Users/uname2", "size": 109338711},
])

df_test["size_kb"] = df_test["size"].astype(int).apply(lambda x: locale.format("%.1f", x / 1024.0, grouping=True) + " KB")
df_test["size_mb"] = df_test["size"].astype(int).apply(lambda x: locale.format("%.1f", x / 1024.0 ** 2, grouping=True) + " MB")
df_test["size_gb"] = df_test["size"].astype(int).apply(lambda x: locale.format("%.1f", x / 1024.0 ** 3, grouping=True) + " GB")

df_test


             dir       size       size_kb   size_mb size_gb
0  /Users/uname1     994933      971.6 KB    0.9 MB  0.0 GB
1  /Users/uname2  109338711  106,776.1 KB  104.3 MB  0.1 GB

[2 rows x 5 columns]

I"ve run this over 120,000 rows and time it takes about 2.97 seconds per column * 3 = ~9 seconds according to %timeit.

Is there anyway I can make this faster? For example, can I instead of returning one column at a time from apply and running it 3 times, can I return all three columns in one pass to insert back into the original dataframe?

The other questions I"ve found all want to take multiple values and return a single value. I want to take a single value and return multiple columns.

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Manuel Emmerson

New York | 2023-01-31

I was preparing for my coding interview, thanks for clarifying this - Return multiple columns from pandas apply() in Python is not the simplest one. Will use it in my bachelor thesis

Anna Wu

Texas | 2023-01-31

Maybe there are another answers? What Return multiple columns from pandas apply() exactly means?. Will use it in my bachelor thesis

Julia Schteiner

Tallinn | 2023-01-31

ast Python module is always a bit confusing 😭 Return multiple columns from pandas apply() is not the only problem I encountered. I am just not quite sure it is the best method

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