convert a dict that contains a tuple of lists to a Data frame?-CodePudding

I have a dict of clusters in the form:

{1: array([[31.47671257, 30.0206217 ],
    [31.49589   , 30.02547   ],
    [31.474725  , 30.025477  ],
    [31.448643  , 30.018775  ],
    [31.486     , 30.014     ],
    [31.438     , 30.002     ],
    [31.461539  , 30.042498  ,....)
2: array([[31.29888   , 29.989722  ],
    [31.31500756, 29.97498111],
    [31.30848442, 30.00917636],
    [31.35363137, 29.97423761],
    [31.318159  , 29.984137  ],
    [31.317     , 29.979063  ],
    [31.312838  , 29.963003  ],
    ) etc.

I want the output to be represented as a data frame like this one:

     Lng       Lat       no_of_Cluster 
0  31.49589   30.02547       1
1  31.474725  30.025477      4
2  31.486     30.014         7

I used this function

df = pd.DataFrame.from_dict(Output, orient='index',columns=['A'])

But this is my output

                        A
1   [[31.47671257, 30.0206217], [31.49589, 30.0254...
2   [[31.29888, 29.989722], [31.31500756, 29.97498...
3   [[31.27858, 29.966307], [31.281, 29.975], [31....
4   [[31.62090813, 30.0946129], [31.74450432, 30.1...
5   [[31.577472, 30.159004], [31.62640129, 30.1430...
6   [[31.2357, 30.0444], [31.23887574, 30.0444], [...
7   [[31.339338, 30.103572], [31.33045708, 30.0610...
8   [[31.30796944, 29.86398859], [31.318988, 29.89...
9   [[31.413884509277, 30.114512733553], [31.34002...
10  [[31.395257, 29.978487], [31.386, 30.05], [31....

How do I convert it?

CodePudding user response：

Try the following:

import pandas as pd

clusters = []
for k,v in data.items():
    df = pd.DataFrame(v, columns=['Lng', 'Lat'])
    df['no_of_Cluster'] = k
    clusters.append(df)
total_df = pd.concat(clusters)
print(total_df)

This will result in

         Lng        Lat  no_of_Cluster
0  31.476713  30.020622              1
1  31.495890  30.025470              1
2  31.474725  30.025477              1
3  31.448643  30.018775              1
4  31.486000  30.014000              1
5  31.438000  30.002000              1
6  31.461539  30.042498              1
0  31.298880  29.989722              2
1  31.315008  29.974981              2
2  31.308484  30.009176              2
3  31.353631  29.974238              2
4  31.318159  29.984137              2
5  31.317000  29.979063              2
6  31.312838  29.963003              2