将行的修改副本添加到数据框中

Question

Let's say we have a data frame below

df = pd.DataFrame(numpy.random.randint(0,5,size=(5, 4)), columns=list('ABCD'))
df
   A  B  C  D
0  3  3  0  0
1  0  3  3  2
2  1  0  0  0
3  2  4  4  0
4  3  2  2  4

I would want to append a new row from the existing data and modify several columns

newrow = df.loc[0].copy()
newrow.A = 99
newrow.B = 90
df.append(newrow)

By doing this I got a warning when trying to modify the row

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
<string>:23: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

1. What would be the clean way of achieving what I intend to do ? I won't have index to use loc because the row is not inside the df yet

2. If later I would like to come back to this row, how could I retrieve its index at the moment of appending.

 newrow = df.loc[0].copy() df.append(newrow) df.loc[which index to use, "A"] = 99

In other words, let's say I would want to add the row first then modify it later, how could I get the added row's index

Answer 1

As I can see, you modify every value of the current df row, so it might unnecessary to copy the current row and get the warning.

Just create a dict with your values and append it to the df :

newrow = {'A':99,'B':90,'C':92, 'D':93}
df = df.append(newrow, ignore_index=True)

Use ignore_index=True and the newrow will just be the last index in your df.

Answer 2

如果您没有使用ignore_index = True提示，请使用df.iloc[-1]查找附加行。