Hope you are having a great weekend. My problem is as follows:

For my designed model i am getting the following predictions:

[0.3182012736797333, 0.6817986965179443, 0.5067878365516663, 0.49321213364601135, 0.4795221984386444, 0.520477831363678, 0.532780110836029, 0.46721988916397095, 0.3282901346683502, 0.6717098355293274]
[0.362120658159256, 0.6378793120384216, 0.5134761929512024, 0.4865237772464752, 0.46048662066459656, 0.539513349533081, 0.5342788100242615, 0.4657211899757385, 0.34932515025138855, 0.6506748199462891]
[0.3647380471229553, 0.6352618932723999, 0.5087167620658875, 0.49128326773643494, 0.4709164798259735, 0.5290834903717041, 0.5408024787902832, 0.4591975510120392, 0.37024226784706116, 0.6297577023506165]
[0.43765324354171753, 0.5623468160629272, 0.505147397518158, 0.49485257267951965, 0.45281311869621277, 0.5471869111061096, 0.5416161417961121, 0.45838382840156555, 0.3789178133010864, 0.6210821866989136]
[0.44772887229919434, 0.5522711277008057, 0.5119441151618958, 0.48805591464042664, 0.46322566270828247, 0.5367743372917175, 0.5402485132217407, 0.45975151658058167, 0.4145151972770691, 0.5854847431182861]
[0.35674020648002625, 0.6432597637176514, 0.48104971647262573, 0.5189502835273743, 0.4554695188999176, 0.54453045129776, 0.5409557223320007, 0.45904430747032166, 0.3258989453315735, 0.6741010546684265]
[0.3909384310245514, 0.609061598777771, 0.4915180504322052, 0.5084819793701172, 0.45033228397369385, 0.5496677160263062, 0.5267384052276611, 0.47326159477233887, 0.34493446350097656, 0.6550655364990234]
[0.32971733808517456, 0.6702827215194702, 0.5224012732505798, 0.47759872674942017, 0.4692566692829132, 0.5307433605194092, 0.5360044836997986, 0.4639955163002014, 0.41811054944992065, 0.5818894505500793]
[0.37096619606018066, 0.6290338039398193, 0.5165190100669861, 0.4834809899330139, 0.4739859998226166, 0.526013970375061, 0.5340168476104736, 0.46598318219184875, 0.3438771069049835, 0.6561229228973389]
[0.4189890921115875, 0.5810109376907349, 0.52749103307724, 0.47250890731811523, 0.44485437870025635, 0.5551456212997437, 0.5398098230361938, 0.46019014716148376, 0.3739124536514282, 0.6260875463485718]
[0.3979812562465668, 0.6020187139511108, 0.5050275325775146, 0.49497246742248535, 0.4653399884700775, 0.5346599817276001, 0.537341833114624, 0.4626581072807312, 0.33742010593414307, 0.6625799536705017]
[0.368088960647583, 0.631911039352417, 0.49925288558006287, 0.5007471442222595, 0.4547160863876343, 0.545283854007721, 0.5408452749252319, 0.45915472507476807, 0.4053747355937958, 0.5946252346038818]

As you can see they are independent lists. I want to convert these lists into a dataframe. Although they are independent, they are coming out of a for loop, so i cannot append them because they are not coming at once.

CodePudding user response：

Use:

data = [[0.3182012736797333, 0.6817986965179443, 0.5067878365516663, 0.49321213364601135, 0.4795221984386444, 0.520477831363678, 0.532780110836029, 0.46721988916397095, 0.3282901346683502, 0.6717098355293274],
[0.362120658159256, 0.6378793120384216, 0.5134761929512024, 0.4865237772464752, 0.46048662066459656, 0.539513349533081, 0.5342788100242615, 0.4657211899757385, 0.34932515025138855, 0.6506748199462891],
[0.3647380471229553, 0.6352618932723999, 0.5087167620658875, 0.49128326773643494, 0.4709164798259735, 0.5290834903717041, 0.5408024787902832, 0.4591975510120392, 0.37024226784706116, 0.6297577023506165],
[0.43765324354171753, 0.5623468160629272, 0.505147397518158, 0.49485257267951965, 0.45281311869621277, 0.5471869111061096, 0.5416161417961121, 0.45838382840156555, 0.3789178133010864, 0.6210821866989136],
[0.44772887229919434, 0.5522711277008057, 0.5119441151618958, 0.48805591464042664, 0.46322566270828247, 0.5367743372917175, 0.5402485132217407, 0.45975151658058167, 0.4145151972770691, 0.5854847431182861],
[0.35674020648002625, 0.6432597637176514, 0.48104971647262573, 0.5189502835273743, 0.4554695188999176, 0.54453045129776, 0.5409557223320007, 0.45904430747032166, 0.3258989453315735, 0.6741010546684265],
[0.3909384310245514, 0.609061598777771, 0.4915180504322052, 0.5084819793701172, 0.45033228397369385, 0.5496677160263062, 0.5267384052276611, 0.47326159477233887, 0.34493446350097656, 0.6550655364990234],
[0.32971733808517456, 0.6702827215194702, 0.5224012732505798, 0.47759872674942017, 0.4692566692829132, 0.5307433605194092, 0.5360044836997986, 0.4639955163002014, 0.41811054944992065, 0.5818894505500793],
[0.37096619606018066, 0.6290338039398193, 0.5165190100669861, 0.4834809899330139, 0.4739859998226166, 0.526013970375061, 0.5340168476104736, 0.46598318219184875, 0.3438771069049835, 0.6561229228973389],
[0.4189890921115875, 0.5810109376907349, 0.52749103307724, 0.47250890731811523, 0.44485437870025635, 0.5551456212997437, 0.5398098230361938, 0.46019014716148376, 0.3739124536514282, 0.6260875463485718],
[0.3979812562465668, 0.6020187139511108, 0.5050275325775146, 0.49497246742248535, 0.4653399884700775, 0.5346599817276001, 0.537341833114624, 0.4626581072807312, 0.33742010593414307, 0.6625799536705017],
[0.368088960647583, 0.631911039352417, 0.49925288558006287, 0.5007471442222595, 0.4547160863876343, 0.545283854007721, 0.5408452749252319, 0.45915472507476807, 0.4053747355937958, 0.5946252346038818]]

# Create this before your for loop
df = pd.DataFrame(columns = range(10))

for pred_list in data:

    #Add this within your for loop
    df = df.append(pd.Series(pred_list), ignore_index=True)

output: