如何从 pandas dataframe 列的列表中提取元素？

Question

I have the following lists:

dates = ['12/29/2020', '12/25/2020', '12/22/2020']
numbers = [ [1, 31, 35], [17, 23, 36], [29, 53, 56] ]

I used them to make a DataFrame:

df = pd.DataFrame(
    {
        'date':dates,
        'nums': numbers
    }
)

This gives me a DataFrame with two columns. I want to break out the elements in the list to create 3 columns (one for each number in the list) to end up with the following DataFrame:

     date            num1 num2 num3 
0    '12/29/2020'    1    31   35
1    '12/25/2020'    17   23   36
2    '12/22/2020'    29   53   56

How can I do this?

Answer 1

Create a new data frame from nums column by converting it to list first, and then concat with date column:

pd.concat([df.date, pd.DataFrame(df.nums.to_list()).add_prefix('num')], axis=1)

         date  num0  num1  num2
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56

Answer 2

Create a new dataframe and join it back:

>>> df[['date']].join(pd.DataFrame(df['num'].tolist()).rename(lambda x: f'num{x + 1}', axis=1))
         date  num1  num2  num3
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56
>>> 

Or just add_prefix :

>>> df[['date']].join(pd.DataFrame(df['num'].tolist()).add_prefix('num'))
         date  num0  num1  num2
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56
>>> 

Answer 3

So the other answers sufficiently cover the case where you need to fix an already existing dataframe , but just in case you have the opportunity, it's much easier to simply fix your data before creating a dataframe:

In [1]: import pandas as pd

In [2]: dates = ['12/29/2020', '12/25/2020', '12/22/2020']

In [3]: numbers = [[1, 31, 35], [17, 23, 36], [29, 53, 56]]

In [4]: nums = {f"num{i}": n for i, n in enumerate(zip(*numbers), 1)}

In [5]: df = pd.DataFrame({"dates": dates, **nums})

In [6]: df
Out[6]:
        dates  num1  num2  num3
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56

Or, another way:

In [7]: data = [[date, *nums] for date, nums in zip(dates, numbers)]

In [8]: pd.DataFrame(data, columns=["dates", "num1", "num2", "num3"])
Out[8]:
        dates  num1  num2  num3
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56

Answer 4

You can use a dataframe constructor like this:

pd.DataFrame(numbers, 
             index=dates, 
             columns=[f'num{i+1}' for i in range(len(numbers))])\
  .rename_axis('dates').reset_index()

Output:

        dates  num1  num2  num3
0  12/29/2020     1    31    35
1  12/25/2020    17    23    36
2  12/22/2020    29    53    56