How to append rows in a pandas dataframe in a for loop?

Question

I have the following for loop:

for i in links:
     data = urllib2.urlopen(str(i)).read()
     data = json.loads(data)
     data = pd.DataFrame(data.items())         


        

Answer 1

There are 2 reasons you may append rows in a loop, 1. add to an existing df, and 2. create a new df.

to create a new df, I think its well documented that you should either create your data as a list and then create the data frame:

cols = ['c1', 'c2', 'c3']
lst = []
for a in range(2):
    lst.append([1, 2, 3])
df1 = pd.DataFrame(lst, columns=cols)
df1
Out[3]: 
   c1  c2  c3
0   1   2   3
1   1   2   3

OR, Create the dataframe with an index and then add to it

cols = ['c1', 'c2', 'c3']
df2 = pd.DataFrame(columns=cols, index=range(2))
for a in range(2):
    df2.loc[a].c1 = 4
    df2.loc[a].c2 = 5
    df2.loc[a].c3 = 6
df2
Out[4]: 
  c1 c2 c3
0  4  5  6
1  4  5  6

If you want to add to an existing dataframe, you could use either method above and then append the df's together (with or without the index):

df3 = df2.append(df1, ignore_index=True)
df3
Out[6]: 
  c1 c2 c3
0  4  5  6
1  4  5  6
2  1  2  3
3  1  2  3

Or, you can also create a list of dictionary entries and append those as in the answer above.

lst_dict = []
for a in range(2):
    lst_dict.append({'c1':2, 'c2':2, 'c3': 3})
df4 = df1.append(lst_dict)
df4
Out[7]: 
   c1  c2  c3
0   1   2   3
1   1   2   3
0   2   2   3
1   2   2   3

Using the dict(zip(cols, vals)))

lst_dict = []
for a in range(2):
    vals = [7, 8, 9]
    lst_dict.append(dict(zip(cols, vals)))
df5 = df1.append(lst_dict)