Convert dict of array of dict to DataFrame - arrays

Question

Here is my timeseries. Timestamp may be either the same or different. I need to convert data to single DataFrame:
{'param1': [
{'ts': 1669246574000, 'value': '6.06'},
{'ts': 1669242973000, 'value': '6.5'}
],
'param2': [
{'ts': 1669246579000, 'value': '7'},
{'ts': 1669242973000, 'value': '5'}
],
}
Update 1: format of DataFrame
ts param1 param2
1669246574000 6.06 1
1669242973000 6.5 2
1669246579000 7 3
1669242973000 5 4
Update 2:
Timestamp (ts) should be index
ts param1 param2
1669242973000 6.5 5
1669246574000 6.06 Nan
1669246579000 Nan 7
Update 3: my solution
data_frames = []
for key, values in data.items():
df = pd.DataFrame(values).set_index('ts').rename(columns={'value': key})
data_frames.append(df)
data_frame = pd.concat(data_frames, axis=1)

Answer 1

Try:
import pandas as pd
data = {
"param1": [
{"ts": 1669246574000, "value": "6.06"},
{"ts": 1669242973000, "value": "6.5"},
],
"param2": [
{"ts": 1669246579000, "value": "7"},
{"ts": 1669242973000, "value": "5"},
],
}
df = pd.concat([pd.DataFrame(v).assign(param=k) for k, v in data.items()])
print(df)
Prints:
ts value param
0 1669246574000 6.06 param1
1 1669242973000 6.5 param1
0 1669246579000 7 param2
1 1669242973000 5 param2
EDIT: With updated question:
import pandas as pd
from itertools import count
data = {
"param1": [
{"ts": 1669246574000, "value": "6.06"},
{"ts": 1669242973000, "value": "6.5"},
],
"param2": [
{"ts": 1669246579000, "value": "7"},
{"ts": 1669242973000, "value": "5"},
],
}
c = count(1)
df = pd.DataFrame(
[
{"ts": d["ts"], "param1": d["value"], "param2": next(c)}
for v in data.values()
for d in v
]
)
print(df)
Prints:
ts param1 param2
0 1669246574000 6.06 1
1 1669242973000 6.5 2
2 1669246579000 7 3
3 1669242973000 5 4