Making lists from pandas.dataframe.iloc slice doesn't work while pandas.dataframe.values slice work

Question

I want to agregate columns from a dataframe into a new columns

So I used:

newdataframe["agregate1"]=list(df.iloc[:,0:4])

but it doesn't work. It returns an ["intensity_x"] list (with x as column index), these strings being the names of my dataframe columns.

While

newdataframe["agregate1"]=list(df.iloc[0,0:4])

will return data such as

[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2920000000.0, 2830000000.0, 3030000000.0, 0.0, 2980000000.0, 3000000000.0].

It is actually important since I can't retrieve correctly my data and it seems like a bug, or I am missing something important.

By reading: pack dataframe columns to list in pandas

I circumvented the problem by using df.values instead of iloc, still I don't understand what is the problem with using "whole slices", only getting headers instead. This is strange. Thanks

Answer 1

If use:

df1 = df.iloc[:,0:4]

output is DataFrame.

If:

df2 = df.iloc[0,0:4]

Output is Series - first row in df and columns 1:4.

Sample:

df = pd.DataFrame({'A':[1,2,3],
                   'B':[4,5,6],
                   'C':[7,8,9],
                   'D':[1,3,5],
                   'E':[5,3,6],
                   'F':[7,4,3]})

print (df)
   A  B  C  D  E  F
0  1  4  7  1  5  7
1  2  5  8  3  3  4
2  3  6  9  5  6  3

df1 = df.iloc[:,0:4]
print (df1)
   A  B  C  D
0  1  4  7  1
1  2  5  8  3
2  3  6  9  5

df2 = df.iloc[0,0:4]
print (df2)
A    1
B    4
C    7
D    1
Name: 0, dtype: int64

Then you can use values if need output as numpy array:

print (df1.values)
[[1 4 7 1]
 [2 5 8 3]
 [3 6 9 5]]

If need output list of lists, use:

print (df1.values.tolist())
[[1, 4, 7, 1], [2, 5, 8, 3], [3, 6, 9, 5]]

If need list in new column:

df['new'] = df.iloc[:,0:4].values.tolist()
print (df)
   A  B  C  D  E  F           new
0  1  4  7  1  5  7  [1, 4, 7, 1]
1  2  5  8  3  3  4  [2, 5, 8, 3]
2  3  6  9  5  6  3  [3, 6, 9, 5]

df['new'] = list(df.iloc[:,0:4].values)
print (df)
   A  B  C  D  E  F           new
0  1  4  7  1  5  7  [1, 4, 7, 1]
1  2  5  8  3  3  4  [2, 5, 8, 3]
2  3  6  9  5  6  3  [3, 6, 9, 5]