Convert 1D list into a (2D) pandas dataframe

Question

I want to convert this list into a pandas dataframe

my_list = [1,2,3,4,5,6,7,8,9]

The dataframe would have 3 columns and 3 rows. I try using

df = pd.DataFrame(my_list, columns = list("abc"))

but it doesn't seem to be working for me.

I'd like to take a poll. If you landed up on this page and the accepted answer was not helpful to you, please ping me and let me know what it is you were searching the answer to. — cs95, Apr 17 '19 at 10:18
yup, converting other types of lists to pandas dataframe. e.g., `list = [['a', 1], ['a', 2], ['b', 1]]` converted to a two-column/Series dataframe — Brian D, Jun 26 '19 at 02:21

score 60 · Accepted Answer · answered Mar 04 '17 at 06:55

60

You need convert list to numpy array and then reshape:

df = pd.DataFrame(np.array(my_list).reshape(3,3), columns = list("abc"))
print (df)
   a  b  c
0  1  2  3
1  4  5  6
2  7  8  9

answered Mar 04 '17 at 06:55

jezrael

score 1 · Answer 2 · answered Jan 20 '23 at 00:29

If you came here looking for a way to convert a Python list into a pandas DataFrame, you may be facing one of the following problems:

If you have a nested list, again, DataFrame constructor works. Make sure that the number of column names are equal to the length of the longest sub-list.
```
col_names = ['col1', 'col2']
df = pd.DataFrame(my_list, columns=col_names)
```

If you want to convert a flat list into a dataframe row, then convert it into a nested list first:
```
df = pd.DataFrame([my_list])
```

If you want to convert a nested list into a DataFrame where each sub-list is a DataFrame column, convert it into a dictionary and cast into a DataFrame. Make sure that the number of column names match the length of the list, i.e. len(col_names) == len(my_list) must be True.
```
col_names = ['col1', 'col2', 'col3']
df = pd.DataFrame(dict(zip(col_names, my_list)))
```

If you want to convert a flat list into a multi-column DataFrame (as in the OP), one way is to transpose the list using iter() and zip() functions and cast to a DataFrame.
```
col_names = ['col1', 'col2', 'col3']
df = pd.DataFrame(zip(*[iter(my_list)]*len(col_names)), columns=col_names)
```

If you want to convert a flat list into a multi-column DataFrame but consecutive values are column values (not row values as above), then you'll have to transpose into a different shape.
```
col_names = ['col1', 'col2', 'col3']
df = pd.DataFrame(zip(*[iter(my_list)]*(len(my_list)//len(col_names))), index=col_names).T
```

2 Answers2