Extracting common values from two data frames

Question

I have an object, "a" made up of spatial coordinates X and Y. The object increases in size over time. After a size increase, object "a" now has new spatial coordinates and I have referred to it as object "b". The coordinate values for both objects are made up horizontal bands of X values; so for each object, the Y values in each band are the same. What I need to do, is make a new data frame comprising all the values of the object "b" data frame for which the X values fall within the same envelope as those for object "a". Consider the objects as two different size footprints. I only need the data which is common to both footprints. The Y value terms are the common factor in each data frame, but the range of X values for each Y value in the data frames varies.

Here's what the two objects look like when they're plotted. Object "a" is the smaller of the two in blue and object "b" is in black.

a<-a
b<-b
plot(b$X,b$Y,cex=0.4,pch=19,col="black")
points(a$X,a$Y,cex=0.4,pch=19,col="blue")

Note: There is a third column ("res") in each data frame. When the new data frame is established I need to carry over the third column of data for those values of object b which are in the object a footprint. I've tried filter using dplyr but I can't seem to get the values from one data frame to filter based on the values of another.

df<-b[b$X <= a$X&a$X <=b$X]
df <- b %>% filter(X<=a$X&a$X>=X)

Per the request below, here are the first two rows of the plot for each object with multiple X values along the same band of Y values. Apologies if this is unwieldy.

a$X          a$Y         a$res
0.09029928  0.015375    157.2284508
0.09079928  0.015375    155.565961
0.09129928  0.015375    156.033599
0.09179928  0.015375    158.22608
0.09229928  0.015375    161.7861875
0.09279928  0.015375    166.4013949
0.09329928  0.015375    171.8005754
0.09379928  0.015375    177.7508019
0.09429928  0.015375    184.0542401
0.09479928  0.015375    190.5451385
0.09529928  0.015375    197.086916
0.09579928  0.015375    203.569351
0.09629928  0.015375    209.9058749
0.09679928  0.015375    216.0309714
0.09729928  0.015375    221.8976859
0.09779928  0.015375    227.4752458
0.09829928  0.015375    232.7467964
0.09879928  0.015375    237.7072531
0.09929928  0.015375    242.3612742
0.09979928  0.015375    246.7213556
0.10029928  0.015375    250.8060511
0.10079928  0.015375    254.6383205
0.10129928  0.015375    258.2440078
0.10179928  0.015375    261.6504535
0.10229928  0.015375    264.8852414
0.10279928  0.015375    267.9750851
0.10329928  0.015375    270.9448547
0.10379928  0.015375    273.8167481
0.10429928  0.015375    276.6096081
0.10479928  0.015375    279.3383892
0.10529928  0.015375    282.0137753
0.10579928  0.015375    284.641953
0.10629928  0.015375    287.2245411
0.10679928  0.015375    289.7586798
0.10729928  0.015375    292.2372832
0.10779928  0.015375    294.649456
0.10829928  0.015375    296.9810784
0.10879928  0.015375    299.2155606
0.10929928  0.015375    301.3347719
0.10979928  0.015375    303.3201437
0.11029928  0.015375    305.1539521
0.11079928  0.015375    306.8207812
0.11129928  0.015375    308.3091696
0.11179928  0.015375    309.613444
0.11229928  0.015375    310.7357413
0.11279928  0.015375    311.6882223
0.11329928  0.015375    312.49548
0.11379928  0.015375    313.1971451
0.11429928  0.015375    313.8506902
0.11479928  0.015375    314.534437
0.11529928  0.015375    315.3507686
0.08581068  0.017375    135.8921899
0.08631068  0.017375    135.6813081
0.08681068  0.017375    135.7108871
0.08731068  0.017375    136.065192
0.08781068  0.017375    136.8065344
0.08831068  0.017375    137.9778373
0.08881068  0.017375    139.6050362
0.08931068  0.017375    141.6993184
0.08981068  0.017375    144.2592074
0.09031068  0.017375    147.2724963
0.09081068  0.017375    150.718035
0.09131068  0.017375    154.5673762
0.09181068  0.017375    158.7862848
0.09231068  0.017375    163.336116
0.09281068  0.017375    168.1750659
0.09331068  0.017375    173.2593009
0.09381068  0.017375    178.5439689
0.09431068  0.017375    183.9840986
0.09481068  0.017375    189.535391
0.09531068  0.017375    195.1549082
0.09581068  0.017375    200.8016635
0.09631068  0.017375    206.4371191
0.09681068  0.017375    212.0255946
0.09731068  0.017375    217.5345922
0.09781068  0.017375    222.9350431
0.09831068  0.017375    228.2014794
0.09881068  0.017375    233.3121371
0.09931068  0.017375    238.2489946
0.09981068  0.017375    242.9977514
0.10031068  0.017375    247.5477517
0.10081068  0.017375    251.8918586
0.10131068  0.017375    256.0262823
0.10181068  0.017375    259.9503683
0.10231068  0.017375    263.6663496
0.10281068  0.017375    267.1790681
0.10331068  0.017375    270.4956703
0.10381068  0.017375    273.6252813
0.10431068  0.017375    276.5786621
0.10481068  0.017375    279.367856
0.10531068  0.017375    282.0058274
0.10581068  0.017375    284.5060987
0.10631068  0.017375    286.8823904
0.10681068  0.017375    289.1482679
0.10731068  0.017375    291.3168014
0.10781068  0.017375    293.4002421
0.10831068  0.017375    295.4097212
0.10881068  0.017375    297.3549752
0.10931068  0.017375    299.2441021
0.10981068  0.017375    301.0833553
0.11031068  0.017375    302.8769776
0.11081068  0.017375    304.6270808
0.11131068  0.017375    306.3335775
0.11181068  0.017375    307.9941667
0.11231068  0.017375    309.6043809
0.11281068  0.017375    311.1576978
0.11331068  0.017375    312.6457221
0.11381068  0.017375    314.0584417
0.11431068  0.017375    315.384564
0.11481068  0.017375    316.6119359
0.11531068  0.017375    317.7280532
0.11581068  0.017375    318.720664
0.11631068  0.017375    319.5784707
0.11681068  0.017375    320.2919353
0.11731068  0.017375    320.8541934
0.11781068  0.017375    321.2620811
0.11831068  0.017375    321.51728
0.11881068  0.017375    321.6275841
0.11931068  0.017375    321.6082958
0.11981068  0.017375    321.4837525
0.12031068  0.017375    321.2889916
0.12081068  0.017375    321.0715562
0.12131068  0.017375    320.8934492
0.12181068  0.017375    320.8332368
0.12231068  0.017375    320.9883102
0.12281068  0.017375    321.4773073
0.12331068  0.017375    322.4427005

b$X           b$Y           b$res
0.0455699   0.015375    74.06596721
0.0460699   0.015375    76.4523308
0.0465699   0.015375    78.53219293
0.0470699   0.015375    80.33607583
0.0475699   0.015375    81.89274681
0.0480699   0.015375    83.22928022
0.0485699   0.015375    84.37111818
0.0490699   0.015375    85.34213004
0.0495699   0.015375    86.16467047
0.0500699   0.015375    86.85963646
0.0505699   0.015375    87.44652295
0.0510699   0.015375    87.94347726
0.0515699   0.015375    88.36735239
0.0520699   0.015375    88.733759
0.0525699   0.015375    89.05711629
0.0530699   0.015375    89.35070163
0.0535699   0.015375    89.6266991
0.0540699   0.015375    89.89624682
0.0545699   0.015375    90.16948314
0.0550699   0.015375    90.45559176
0.0555699   0.015375    90.76284569
0.0560699   0.015375    91.09865007
0.0565699   0.015375    91.46958399
0.0570699   0.015375    91.88144114
0.0575699   0.015375    92.33926948
0.0580699   0.015375    92.84740977
0.0585699   0.015375    93.40953312
0.0590699   0.015375    94.02867748
0.0595699   0.015375    94.70728314
0.0600699   0.015375    95.44722718
0.0605699   0.015375    96.24985697
0.0610699   0.015375    97.11602266
0.0615699   0.015375    98.04610876
0.0620699   0.015375    99.04006465
0.0625699   0.015375    100.0974343
0.0630699   0.015375    101.2173848
0.0635699   0.015375    102.3987345
0.0640699   0.015375    103.6399795
0.0645699   0.015375    104.9393198
0.0650699   0.015375    106.2946845
0.0655699   0.015375    107.7037558
0.0660699   0.015375    109.1639927
0.0665699   0.015375    110.6726532
0.0670699   0.015375    112.2268162
0.0675699   0.015375    113.8234023
0.0680699   0.015375    115.459194
0.0685699   0.015375    117.1308547
0.0690699   0.015375    118.8349475
0.0695699   0.015375    120.5679527
0.0700699   0.015375    122.3262849
0.0705699   0.015375    124.1063092
0.0710699   0.015375    125.9043566
0.0715699   0.015375    127.7167387
0.0720699   0.015375    129.5397621
0.0725699   0.015375    131.3697412
0.0730699   0.015375    133.2030114
0.0735699   0.015375    135.0359408
0.0740699   0.015375    136.8649415
0.0745699   0.015375    138.6864806
0.0750699   0.015375    140.4970898
0.0755699   0.015375    142.2933753
0.0760699   0.015375    144.0720262
0.0765699   0.015375    145.8298229
0.0770699   0.015375    147.5636449
0.0775699   0.015375    149.2704775
0.0780699   0.015375    150.9474186
0.0785699   0.015375    152.5916844
0.0790699   0.015375    154.2006151
0.0795699   0.015375    155.7716795
0.0800699   0.015375    157.3024795
0.0805699   0.015375    158.790754
0.0810699   0.015375    160.2343822
0.0815699   0.015375    161.6313866
0.0820699   0.015375    162.9799354
0.0825699   0.015375    164.2783442
0.0830699   0.015375    165.5250783
0.0835699   0.015375    166.7187531
0.0840699   0.015375    167.858135
0.0845699   0.015375    168.9421419
0.0850699   0.015375    169.9698431
0.0855699   0.015375    170.9404585
0.0860699   0.015375    171.8533582
0.0865699   0.015375    172.7080612
0.0870699   0.015375    173.5042336
0.0875699   0.015375    174.2416873
0.0880699   0.015375    174.9203774
0.0885699   0.015375    175.5403999
0.0890699   0.015375    176.1019887
0.0895699   0.015375    176.6055133
0.0900699   0.015375    177.0514745
0.0905699   0.015375    177.4405016
0.0910699   0.015375    177.7733483
0.0915699   0.015375    178.0508888
0.0920699   0.015375    178.2741135
0.0925699   0.015375    178.4441243
0.0930699   0.015375    178.5621305
0.0935699   0.015375    178.6294436
0.0940699   0.015375    178.6474724
0.0945699   0.015375    178.6177179
0.0950699   0.015375    178.5417678
0.0955699   0.015375    178.4212916
0.0960699   0.015375    178.2580344
0.0965699   0.015375    178.0538118
0.0970699   0.015375    177.810504
0.0975699   0.015375    177.5300496
0.0980699   0.015375    177.2144405
0.0985699   0.015375    176.8657153
0.0990699   0.015375    176.4859534
0.0995699   0.015375    176.0772692
0.1000699   0.015375    175.6418062
0.1005699   0.015375    175.1817303
0.1010699   0.015375    174.6992244
0.1015699   0.015375    174.1964822
0.1020699   0.015375    173.675702
0.1025699   0.015375    173.1390809
0.1030699   0.015375    172.5888089
0.1035699   0.015375    172.027063
0.1040699   0.015375    171.4560017
0.1045699   0.015375    170.8777588
0.1050699   0.015375    170.2944383
0.1055699   0.015375    169.7081088
0.1060699   0.015375    169.1207982
0.1065699   0.015375    168.5344883
0.1070699   0.015375    167.9511102
0.1075699   0.015375    167.372539
0.1080699   0.015375    166.8005894
0.1085699   0.015375    166.2370111
0.1090699   0.015375    165.6834844
0.1095699   0.015375    165.1416163
0.1100699   0.015375    164.6129364
0.1105699   0.015375    164.0988936
0.1110699   0.015375    163.6008524
0.1115699   0.015375    163.1200901
0.1120699   0.015375    162.6577937
0.1125699   0.015375    162.2150575
0.1130699   0.015375    161.7928806
0.1135699   0.015375    161.3921656
0.1140699   0.015375    161.0137162
0.1145699   0.015375    160.6582364
0.1150699   0.015375    160.3263295
0.1155699   0.015375    160.0184976
0.1160699   0.015375    159.735141
0.1165699   0.015375    159.4765591
0.1170699   0.015375    159.2429503
0.1175699   0.015375    159.0344135
0.1180699   0.015375    158.8509493
0.1185699   0.015375    158.6924617
0.1190699   0.015375    158.558761
0.1195699   0.015375    158.4495657
0.1200699   0.015375    158.3645068
0.1205699   0.015375    158.3031304
0.1210699   0.015375    158.2649028
0.1215699   0.015375    158.2492148
0.1220699   0.015375    158.2553872
0.1225699   0.015375    158.2826761
0.1230699   0.015375    158.3302801
0.1235699   0.015375    158.3973462
0.1240699   0.015375    158.4829779
0.1245699   0.015375    158.5862433
0.1250699   0.015375    158.7061833
0.1255699   0.015375    158.841821
0.1260699   0.015375    158.9921719
0.1265699   0.015375    159.156254
0.1270699   0.015375    159.3330989
0.1275699   0.015375    159.5217642
0.1280699   0.015375    159.7213453
0.1285699   0.015375    159.9309888
0.1290699   0.015375    160.1499064
0.1295699   0.015375    160.3773894
0.1300699   0.015375    160.6128241
0.1305699   0.015375    160.8557075
0.1310699   0.015375    161.1056643
0.1315699   0.015375    161.3624643
0.1320699   0.015375    161.6260408
0.1325699   0.015375    161.8965093
0.1330699   0.015375    162.1741879
0.1335699   0.015375    162.4596173
0.1340699   0.015375    162.7535828
0.1345699   0.015375    163.0571361
0.1350699   0.015375    163.3716191
0.1355699   0.015375    163.698687
0.1360699   0.015375    164.0403341
0.1365699   0.015375    164.3989187
0.1370699   0.015375    164.7771902
0.1375699   0.015375    165.1783166
0.1380699   0.015375    165.6059126
0.1385699   0.015375    166.0640694
0.1390699   0.015375    166.5573848
0.1395699   0.015375    167.0909942
0.1400699   0.015375    167.6706035
0.1405699   0.015375    168.3025216
0.1410699   0.015375    168.9936948
0.1415699   0.015375    169.7517423
0.1420699   0.015375    170.584992
0.1425699   0.015375    171.5025179
0.1430699   0.015375    172.5141784
0.1435699   0.015375    173.6306555
0.1440699   0.015375    174.8634954
0.1445699   0.015375    176.2251495
0.1450699   0.015375    177.7290177
0.1455699   0.015375    179.3894911
0.1460699   0.015375    181.2219976
0.1465699   0.015375    183.2430474
0.1470699   0.015375    185.4702797
0.1475699   0.015375    187.9225117
0.1480699   0.015375    190.6197872
0.1485699   0.015375    193.5834271
0.1490699   0.015375    196.8360819
0.1495699   0.015375    200.4017834
0.1500699   0.015375    204.3059998
0.1505699   0.015375    208.5756905
0.1510699   0.015375    213.2393628
0.1515699   0.015375    218.3271296
0.1520699   0.015375    223.8707687
0.1525699   0.015375    229.9037829
0.1530699   0.015375    236.4614616
0.1535699   0.015375    243.580944
0.0431782   0.017375    80.64599005
0.0436782   0.017375    81.56249763
0.0441782   0.017375    82.34194793
0.0446782   0.017375    83.00074446
0.0451782   0.017375    83.55433555
0.0456782   0.017375    84.01724695
0.0461782   0.017375    84.40311369
0.0466782   0.017375    84.72471138
0.0471782   0.017375    84.99398684
0.0476782   0.017375    85.22208812
0.0481782   0.017375    85.41939391
0.0486782   0.017375    85.59554233
0.0491782   0.017375    85.75945909
0.0496782   0.017375    85.91938509
0.0501782   0.017375    86.0829034
0.0506782   0.017375    86.25696566
0.0511782   0.017375    86.44791786
0.0516782   0.017375    86.66152564
0.0521782   0.017375    86.90299888
0.0526782   0.017375    87.17701585
0.0531782   0.017375    87.4877467
0.0536782   0.017375    87.83887648
0.0541782   0.017375    88.23362756
0.0546782   0.017375    88.6747815
0.0551782   0.017375    89.16470041
0.0556782   0.017375    89.70534777
0.0561782   0.017375    90.29830876
0.0566782   0.017375    90.94480995
0.0571782   0.017375    91.64573865
0.0576782   0.017375    92.4016616
0.0581782   0.017375    93.21284324
0.0586782   0.017375    94.07926345
0.0591782   0.017375    95.00063484
0.0596782   0.017375    95.97641948
0.0601782   0.017375    97.00584525
0.0606782   0.017375    98.08792159
0.0611782   0.017375    99.22145494
0.0616782   0.017375    100.4050635
0.0621782   0.017375    101.6371919
0.0626782   0.017375    102.916125
0.0631782   0.017375    104.2400012
0.0636782   0.017375    105.6068262
0.0641782   0.017375    107.014485
0.0646782   0.017375    108.4607546
0.0651782   0.017375    109.9433155
0.0656782   0.017375    111.4597633
0.0661782   0.017375    113.0076196
0.0666782   0.017375    114.5843425
0.0671782   0.017375    116.1873373
0.0676782   0.017375    117.8139653
0.0681782   0.017375    119.4615545
0.0686782   0.017375    121.1274073
0.0691782   0.017375    122.8088102
0.0696782   0.017375    124.5030416
0.0701782   0.017375    126.2073798
0.0706782   0.017375    127.9191104
0.0711782   0.017375    129.6355339
0.0716782   0.017375    131.3539723
0.0721782   0.017375    133.0717755
0.0726782   0.017375    134.7863279
0.0731782   0.017375    136.4950537
0.0736782   0.017375    138.1954231
0.0741782   0.017375    139.8849568
0.0746782   0.017375    141.5612315
0.0751782   0.017375    143.2218843
0.0756782   0.017375    144.8646169
0.0761782   0.017375    146.4871996
0.0766782   0.017375    148.0874752
0.0771782   0.017375    149.6633624
0.0776782   0.017375    151.2128587
0.0781782   0.017375    152.7340435
0.0786782   0.017375    154.225081
0.0791782   0.017375    155.6842219
0.0796782   0.017375    157.109806
0.0801782   0.017375    158.5002641
0.0806782   0.017375    159.8541191
0.0811782   0.017375    161.1699881
0.0816782   0.017375    162.4465829
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0.0991782   0.017375    179.2947862
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0.1001782   0.017375    178.8184826
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0.1026782   0.017375    177.2184998
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0.1446782   0.017375    184.8905363
0.1451782   0.017375    186.220915
0.1456782   0.017375    187.6304233
0.1461782   0.017375    189.12514
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0.1476782   0.017375    194.1881852
0.1481782   0.017375    196.0938141
0.1486782   0.017375    198.1222021
0.1491782   0.017375    200.2824447
0.1496782   0.017375    202.58422
0.1501782   0.017375    205.0378128
0.1506782   0.017375    207.6541397
0.1511782   0.017375    210.4447738
0.1516782   0.017375    213.4219715
0.1521782   0.017375    216.5986986
0.1526782   0.017375    219.9886574
0.1531782   0.017375    223.6063148
0.1536782   0.017375    227.4669303
0.1541782   0.017375    231.5865852
0.1546782   0.017375    235.9822118
0.1551782   0.017375    240.6716242
0.1556782   0.017375    245.6735485
0.1561782   0.017375    251.0076548
0.1566782   0.017375    256.6945888

Answer 1

A data.table solution, could probably be more elegant, but should get the job done.

library(data.table)

## setDT() necessary if a and b are standard R data.frame objects
setDT(a)
setDT(b)

## Make a range summary table for a, grouped by Y, and set the key, Y
a_range <- a[,.(min_X_a = min(X),
                max_X_a = max(X)), keyby = .(Y)]

## Set key for b as Y
setkey(b,Y)

## Join the two tables, subset where the range conditions are met,
## and delete the min/max summary columns
c <- b[a_range][X > min_X_a 
                & X < max_X_a][,c("min_X_a","max_X_a") := NULL]

Formatting note:

Please edit the code below so that it provides a simplified sample set of two data.frames and their expected output. This will allow others to help solve your problem without needing to spend time wrangling the sample data into something R readable.

 # Set 'a'
a <- data.frame(X   = c(1,2,3,1,2),
                Y   = c(1,1,1,2,2),
                res = c(1,2,3,4,5))

# Set 'b'              
b <- data.frame(X   = c(0.5, 1.0, 2.5, 2.0, 3.5),
                Y   = c(1,1,1,2,2),
                res = c(6,7,8,9,10))

## Expected Result
c <- data.frame(X = c(1.0,2.5,2.0),
                Y = c(1,1,2),
                res = c(7,8,9))