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stackoverflow.com › questions › 39551566 › create-a-set-from-a-series-in-pandas

If you only need to get list of unique values, you can just use unique method. If you want to have Python's set, then do set(some_series)

In [1]: s = pd.Series([1, 2, 3, 1, 1, 4])

In [2]: s.unique()
Out[2]: array([1, 2, 3, 4])

In [3]: set(s)
Out[3]: {1, 2, 3, 4}

However, if you have DataFrame, just select series out of it ( some_data_frame['<col_name>'] ).

Answer from grechut on Stack Overflow

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stackoverflow.com › questions › 39551566 › create-a-set-from-a-series-in-pandas

python - Create a set from a series in pandas - Stack Overflow

Top answer

1 of 2

120

If you only need to get list of unique values, you can just use unique method. If you want to have Python's set, then do set(some_series)

In [1]: s = pd.Series([1, 2, 3, 1, 1, 4])

In [2]: s.unique()
Out[2]: array([1, 2, 3, 4])

In [3]: set(s)
Out[3]: {1, 2, 3, 4}

However, if you have DataFrame, just select series out of it ( some_data_frame['<col_name>'] ).

2 of 2

43

With large size series with duplicates the set(some_series) execution-time will evolve exponentially with series size.

Better practice would be to set(some_series.unique()).

A simple exemple showing x16 execution time.

Pandas

pandas.pydata.org › docs › reference › api › pandas.DataFrame.set_index.html

pandas.DataFrame.set_index — pandas 3.0.3 documentation

Whether to append columns to existing index. Setting to True will add the new columns to existing index.

Discussions

Convert dataframe rows into sets

I'm curious what you want this for! I've assumed your dataframe comes with each of your variables in their own column so this starts with a bit to combine a row into a tuple. Then it aggregates the tuples belonging to each set. #Make your example dataframe data=[["set1","a",9,10], ["set1","b",14,100], ["set2","c",5,69], ["set2","d",4,100]] df=pd.DataFrame(columns=["Set","var1","var2","var3"],data=data) #turn your columns into tuples df["tuple"]=list(df[["var1","var2","var3"]].to_records()) #combine df=df.groupby("Set")["tuple"].agg(lambda x: [y for y in x]).reset_index() More on reddit.com

r/learnpython

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June 30, 2021

python - Set value on an entire column of a pandas dataframe - Stack Overflow

I'm trying to set the entire column of a dataframe to a specific value. In [1]: df Out [1]: issueid industry 0 001 xxx 1 002 xxx 2 003 xxx 3 004 xxx 4 005 xxx · From what I've seen, loc is the best practice when replacing values in a dataframe (or isn't it?): ... A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_index,col_indexer] = value instead ... I got the same warning message. Any ideas? Working with Python 3.5.2 and pandas ... More on stackoverflow.com

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python - How to set the columns in pandas - Stack Overflow

Here is my dataframe: Dec-18 Jan-19 Feb-19 Mar-19 Apr-19 May-19 Saturday 2540.0 2441.0 3832.0 4093.0 1455.0 2552.0 Sunday 1313.0 1891.0 2968.0 2260.0 1454.0 1798.0 More on stackoverflow.com

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July 2, 2019

Convert dataframe rows into sets : r/learnpython

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