Iterate over one dataframe and add values to another dataframe without "append" or "concat"? - pandas

Question

I have a dataframe "df_edges" where I want to iterate over.
Inside the iteration is an if/else and a string split. I need to add the values from the if/else into a new dataframe (each iteration = one new row in the other dataframe).
Example data of "df_edges":
+-----------------------------------------+
| channelId ... featuredChannelsUrlsCount |
+-----------------------------------------+
| 0 UC-ry8ngUIJHTMBWeoARZGmA ... 1 |
| 1 UC-zK3cJdazy01AKTu8g_amg ... 6 |
| 2 UC05_iIGvXue0sR01JNpRHzw ... 10 |
| 3 UC141nSav5cjmTXN7B70ts0g ... 0 |
| 4 UC1cQzKmbx9x0KipvoCt4NJg ... 0 |
+-----------------------------------------+
# new empty dataframe where I want to add the values
df_edges_to_db = pd.DataFrame(columns=["Source", "Target"])
#iteration over the dataframe
for row in df_edges.itertuples():
if row.featuredChannelsUrlsCount != 0:
featured_channels = row[2].split(',')
for fc in featured_channels:
writer.writerow([row[1], fc])
df_edges_to_db = df_edges_to_db.append({"Source": row[1], "Target": fc}, ignore_index=True)
else:
writer.writerow([row[1], row[1]])
df_edges_to_db = df_edges_to_db.append({"Source": row[1], "Target": row[1]}, ignore_index=True)
This seems to work. But the documentation says (https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.append.html):
The following, while not recommended methods for generating DataFrames
So, is there a more "best practice" way (besides append/concat) to add the rows with the values?

Answer 1

Here is possible create list of dictionaries by python append, not DataFrame.append like in your solution, and the call only once DataFrame constructor:
L = []
#iteration over the dataframe
for row in df_edges.itertuples():
if row.featuredChannelsUrlsCount != 0:
featured_channels = row[2].split(',')
for fc in featured_channels:
writer.writerow([row[1], fc])
L.append({"Source": row[1], "Target": fc})
else:
writer.writerow([row[1], row[1]])
L.append({"Source": row[1], "Target": row[1]})
df_edges_to_db = pd.DataFrame(L)

Answer 2

Actually I am not clear how your df_edges dataFrame looks like. By looking your code I will suggest you to replace your body of outer for-loop with something like this :
new_list= [someOperationOn(x) if x==0 else otherOperationOn(x) for x in mylist]