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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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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
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
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