Efficient insertion of named tuple into pandas data frame

Question

I have a named tuple called "rows" if I print it, it would look as shown below. How do I efficiently (not in for loop) insert this into a pandas data frame so that I can use it to plot graphs. (Number of rows and columns can go more than a thousand sometimes)

for row in rows:
    print (row[0], row[1])

Output:

2016-01-04    00:00:00.000000000
2016-01-04    00:01:00.000000000
2016-01-04    00:02:00.000000000
2016-01-04    00:03:00.000000000
2016-01-04    00:04:00.000000000
2016-01-04    00:05:00.000000000

`pd.DataFrame(rows)`? Or if this data came from somewhere, perhaps that might be of use. — Mateen Ulhaq, Jan 09 '20 at 09:35
@mateen-ulhaq actually `rows` is a result of a `cassandra` database `cql` query. — reddi hari, Jan 09 '20 at 11:24

score 1 · Answer 1 · answered Jan 09 '20 at 09:38

1

The loop is long two steps only independently of the length of rows:

pd.DataFrame([i for i in zip(*rows)])

answered Jan 09 '20 at 09:38

jimifiki

5,377
2
34
60

Thank you, But when I print the dataframe `print(df)` both the answers gives the output `Empty DataFrame` – reddi hari Jan 09 '20 at 12:01

score 1 · Answer 2 · answered Jan 09 '20 at 09:39

1

Why not just try:

df = pd.DataFrame(rows)

answered Jan 09 '20 at 09:39

U13-Forward

69,221
14
89
114

Efficient insertion of named tuple into pandas data frame

2 Answers2