How to pass each row of a dataFrame to an array

Question

How to add a dataframe row in a field array Like i have my data frame.

import pandas as pd
inp = [{'c1':10, 'c2':100}, {'c1':11,'c2':110}, {'c1':12,'c2':120}]
df = pd.DataFrame(inp)
print df

Output:

So i want to have something like this :

{
  "fields": {
        "c1": 10,
        "c2": 100,
   }
},
{
  "fields": {
        "c1": 11,
        "c2": 110,
   }
},
{
  "fields": {
        "c1": 12,
        "c2": 120,
   }
}

How can i do it ?

user15270287 · Answer 1 · 2021-03-07T16:33:59.427

6

You can do:

a = df.transpose().to_dict()
a
>>> {0: {'c1': 10, 'c2': 100}, 1: {'c1': 11, 'c2': 110}, 2: {'c1': 12, 'c2': 120}}
res = [{'fields': a[i]} for i in a]
res
>>> [{'fields': {'c1': 10, 'c2': 100}}, {'fields': {'c1': 11, 'c2': 110}}, {'fields': {'c1': 12, 'c2': 120}}]

As @anky points out, defining a like so: a = df.to_dict('index') will also work, not sure which is more computationally efficient

edited Mar 07 '21 at 16:33

answered Mar 07 '21 at 16:29

user15270287

1,123
4
11

This method changes my column date to timestamp.From 2020-01-03 to Timestamp('2020-01-03 00:00:00'),How can i fix that – Ekane 3 Mar 07 '21 at 23:30
https://stackoverflow.com/questions/34386751/pandas-convert-timestamp-to-datetime-date – user15270287 Mar 08 '21 at 16:11

score 4 · Answer 2 · answered Mar 07 '21 at 16:34

You can try using df.to_dict with orient as records.

out = df.to_dict(orient='records')
# [{'c1': 10, 'c2': 100}, {'c1': 11, 'c2': 110}, {'c1': 12, 'c2': 120}]
out = [{'fields': val} for val in out]

[{'fields': {'c1': 10, 'c2': 100}},
 {'fields': {'c1': 11, 'c2': 110}},
 {'fields': {'c1': 12, 'c2': 120}}]

BENY · Accepted Answer · 2021-03-08T01:19:15.683

3

Try chain with df.to_dict

d = [{'field' : x} for x in df.to_dict('records')]
Out[167]: 
[{'field': {'c1': 10, 'c2': 100}},
 {'field': {'c1': 11, 'c2': 110}},
 {'field': {'c1': 12, 'c2': 120}}]

edited Mar 08 '21 at 01:19

answered Mar 07 '21 at 16:56

BENY

317,841
20
164
234

I guess using short-forms is scheduled for deprecation in the next version. Might want to mention it as in newer versions it might raise `Exception`, the latest version throws `FutureWarning`. Works like charm in older versions. – Ch3steR Mar 07 '21 at 17:06
Thanks BENY, but 'r' parameter is deprecated as Ch3steR said.So i changed the 'r' to 'records' and it worked perfectly .Thanks – Ekane 3 Mar 07 '21 at 23:04

score 1 · Answer 4 · answered Mar 07 '21 at 16:51

Pandas' built in method to_dict() allows converting a dataframe to a serialized list of records. Your desired output would require a transformation on these records:

# Get each row as a record
records = df.to_dict(orient='records')
# [{'c1': 10, 'c2': 100}, {'c1': 11, 'c2': 110}, {'c1': 12, 'c2': 120}]

# Transform each row
records = [{'fields':x} for x in records]
# [{'fields': {'c1': 10, 'c2': 100}},
# {'fields': {'c1': 11, 'c2': 110}},
# {'fields': {'c1': 12, 'c2': 120}}]

How to pass each row of a dataFrame to an array

4 Answers4