How to form tuple column from two columns in Pandas

Question

I ve got a Pandas DataFrame and I want to combine the  lat  and  long  columns to form a tuple    lt class  pandas core frame DataFrame  gt  Int64Index  205482 entries  0 to 209018 Data columns  Month           205482  non-null values Reported by     205482  non-null values Falls within    205482  non-null values Easting         205482  non-null values Northing        205482  non-null values Location        205482  non-null values Crime type      205482  non-null values long            205482  non-null values lat             205482  non-null values dtypes  float64 4   object 5    The code I tried to use was   def merge two cols series        return  series  lat    series  long     sample  lat long     sample apply merge two cols  axis 1    However  this returned the following error   ---------------------------------------------------------------------------  AssertionError                            Traceback  most recent call last   lt ipython-input-261-e752e52a96e6 gt  in  lt module gt          2     return  series  lat    series  long          3  ---- gt  4 sample  lat long     sample apply merge two cols  axis 1        5        AssertionError  Block shape incompatible with manager    How can I solve this problem

User · Answer

In  10   df Out 10             A         B       lat      long 0  1 428987  0 614405  0 484370 -0 628298 1 -0 485747  0 275096  0 497116  1 047605 2  0 822527  0 340689  2 120676 -2 436831 3  0 384719 -0 042070  1 426703 -0 634355 4 -0 937442  2 520756 -1 662615 -1 377490 5 -0 154816  0 617671 -0 090484 -0 191906 6 -0 705177 -1 086138 -0 629708  1 332853 7  0 637496 -0 643773 -0 492668 -0 777344 8  1 109497 -0 610165  0 260325  2 533383 9 -1 224584  0 117668  1 304369 -0 152561  In  11   df  lat long     df   lat    long    apply tuple  axis 1   In  12   df Out 12             A         B       lat      long                             lat long 0  1 428987  0 614405  0 484370 -0 628298       0 484370195967  -0 6282975278  1 -0 485747  0 275096  0 497116  1 047605       0 497115615839  1 04760475074  2  0 822527  0 340689  2 120676 -2 436831       2 12067574274  -2 43683074367  3  0 384719 -0 042070  1 426703 -0 634355       1 42670326172  -0 63435462504  4 -0 937442  2 520756 -1 662615 -1 377490      -1 66261469102  -1 37749004179  5 -0 154816  0 617671 -0 090484 -0 191906   -0 0904840623396  -0 191905582481  6 -0 705177 -1 086138 -0 629708  1 332853      -0 629707821728  1 33285348929  7  0 637496 -0 643773 -0 492668 -0 777344    -0 492667604075  -0 777344111021  8  1 109497 -0 610165  0 260325  2 533383         0 26032456699  2 5333825651  9 -1 224584  0 117668  1 304369 -0 152561      1 30436900612  -0 152560909725

User · Answer

I d like to add df values tolist     as long as you don t mind to get a column of lists rather than tuples   import pandas as pd import numpy as np  size   int 1e 07  df   pd DataFrame   a   np random rand size    b   np random rand size       timeit df values tolist   1 47 s    38 9 ms per loop  mean    std  dev  of 7 runs  1 loop each    timeit list zip df a df b   1 92 s    131 ms per loop  mean    std  dev  of 7 runs  1 loop each

User · Answer

Get comfortable with zip  It comes in handy when dealing with column data    df  new col     list zip df lat  df long     It s less complicated and faster than using apply or map  Something like np dstack is twice as fast as zip  but wouldn t give you tuples

User · Answer

Pandas has the itertuples method to do exactly this   list df   lat    long    itertuples index False  name None

[python] How to form tuple column from two columns in Pandas

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