In [1]:

    

import itertools
import os
import numpy as np
import pandas as pd



# Get the root_path for this jupyter notebook repo.
repo_path = os.path.dirname(os.path.abspath(os.getcwd()))

path_files_locus_index = os.path.join(
    repo_path, 'files', 'tell-dor', 'tell-dor-area-g-locus-image-index.csv'
)

# Path to the Tell Dor file metadata CSV
path_files = os.path.join(
    repo_path, 'files', 'tell-dor', 'tell-dor-files.csv'
)
# Path to the Tell Dor locus metadata CSV 
path_loci = os.path.join(
    repo_path, 'files', 'tell-dor', 'tell-dor-loci.csv'
)
# Output path for associations between the files and the loci.
path_files_contexts = os.path.join(
    repo_path, 'files', 'tell-dor', 'tell-dor-files-contexts.csv'
)


# Read the file - locus index supplied by the Tell Dor team.
fl_df = pd.read_csv(path_files_locus_index)

# Read the file metadata CSV into dataframe f_df.
f_df = pd.read_csv(path_files)

# Read the locus (and wall) CSV into dataframe l_df.
l_df = pd.read_csv(path_loci)

fl_df['Locus_Wall'] = fl_df['Locus_Wall'].astype(str) 
fl_df['Locus ID'] = np.nan
for i, row in fl_df.iterrows():
    wall_id = 'Wall ' + row['Locus_Wall']
    locus_id = 'Locus ' + row['Locus_Wall']
    print('Look for {} or {}'.format(wall_id, locus_id))
    id_indx = ((l_df['Locus ID']==wall_id)|(l_df['Locus ID']==locus_id))
    if l_df[id_indx].empty:
        continue
    up_indx = (fl_df['Locus_Wall'] == row['Locus_Wall'])
    fl_df.loc[up_indx, 'Locus ID'] = l_df[id_indx]['Locus ID'].iloc[0]
    print('Update {} with {}'.format(row['Locus_Wall'], l_df[id_indx]['Locus ID'].iloc[0]))

fl_df.to_csv(path_files_locus_index, index=False)



# Set up a dict for File and Locus (and Wall) associations.
file_locus_data = {
    'File ID':[], 
    'Locus ID': [],
}

# Set up a dict for File and Area associations.
# NOTE: An "Area" is an aggregation of multiple squares in the locus/wall
# datafile. Eric grouped these to make search / browsing easier. They
# don't really have any purpose or value for interpretation.
file_square_data = {
    'File ID':[], 
    'Area': [],
}


def add_to_file_context_data(
    file_ids, 
    context_ids,  
    data,
    context_id_col='Locus ID'
):
    """Adds records of file and context associations to a data dict"""
    if not isinstance(context_ids, list):
        context_ids = [context_ids]
    # Get the cross product of all the file_ids and the
    # context_ids
    crossprod = list(itertools.product(file_ids, context_ids))
    data['File ID'] += [c[0] for c in crossprod]
    data[context_id_col] += [c[1] for c in crossprod]
    return data


    

    




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Look for Wall 9066 or Locus 9066
Update 9066 with Wall 9066
Look for Wall 9140 or Locus 9140
Look for Wall 9436 or Locus 9436
Update 9436 with Locus 9436
Look for Wall 9066 or Locus 9066
Update 9066 with Wall 9066
Look for Wall 9211 or Locus 9211
Update 9211 with Wall 9211
Look for Wall 9861 or Locus 9861
Update 9861 with Locus 9861
Look for Wall 9066 or Locus 9066
Update 9066 with Wall 9066
Look for Wall 9140 or Locus 9140
Look for Wall 9902 or Locus 9902
Update 9902 with Locus 9902
Look for Wall 9914 or Locus 9914
Update 9914 with Wall 9914
Look for Wall 9211 or Locus 9211
Update 9211 with Wall 9211
Look for Wall 9140 or Locus 9140
Look for Wall 9859 or Locus 9859
Update 9859 with Locus 9859
Look for Wall 9066 or Locus 9066
Update 9066 with Wall 9066
Look for Wall 18015 or Locus 18015
Update 18015 with Locus 18015
Look for Wall 18019 or Locus 18019
Update 18019 with Locus 18019
Look for Wall 9065 or Locus 9065
Update 9065 with Wall 9065
Look for Wall 9066 or Locus 9066
Update 9066 with Wall 9066
Look for Wall 9400 or Locus 9400
Update 9400 with Wall 9400
Look for Wall 9400 or Locus 9400
Update 9400 with Wall 9400
Look for Wall 9140 or Locus 9140
Look for Wall 9915 or Locus 9915
Update 9915 with Wall 9915
Look for Wall 04G0-004 or Locus 04G0-004
Update 04G0-004 with Locus 04G0-004
Look for Wall 04G0-013 or Locus 04G0-013
Update 04G0-013 with Locus 04G0-013
Look for Wall 18384 or Locus 18384
Update 18384 with Locus 18384
Look for Wall 18396 or Locus 18396
Update 18396 with Locus 18396
Look for Wall 9903 or Locus 9903
Update 9903 with Locus 9903
Look for Wall 9795 or Locus 9795
Update 9795 with Locus 9795
Look for Wall 04G0-013 or Locus 04G0-013
Update 04G0-013 with Locus 04G0-013
Look for Wall 18265 or Locus 18265
Update 18265 with Locus 18265
Look for Wall 18242 or Locus 18242
Update 18242 with Locus 18242
Look for Wall 18076 or Locus 18076
Update 18076 with Locus 18076
Look for Wall 9795 or Locus 9795
Update 9795 with Locus 9795
Look for Wall 18058 or Locus 18058
Update 18058 with Locus 18058
Look for Wall 9795 or Locus 9795
Update 9795 with Locus 9795
Look for Wall 18033 or Locus 18033
Update 18033 with Locus 18033
Look for Wall 9816 or Locus 9816
Update 9816 with Locus 9816
Look for Wall 18242 or Locus 18242
Update 18242 with Locus 18242
Look for Wall 18265 or Locus 18265
Update 18265 with Locus 18265
Look for Wall 18033 or Locus 18033
Update 18033 with Locus 18033
Look for Wall 18273 or Locus 18273
Update 18273 with Locus 18273
Look for Wall 18265 or Locus 18265
Update 18265 with Locus 18265
Look for Wall 18033 or Locus 18033
Update 18033 with Locus 18033
Look for Wall 9902 or Locus 9902
Update 9902 with Locus 9902
Look for Wall 18216 or Locus 18216
Update 18216 with Locus 18216
Look for Wall 18570 or Locus 18570
Update 18570 with Locus 18570
Look for Wall 18058 or Locus 18058
Update 18058 with Locus 18058
Look for Wall 18242 or Locus 18242
Update 18242 with Locus 18242
Look for Wall 18395 or Locus 18395
Update 18395 with Locus 18395
Look for Wall 10D2-516 or Locus 10D2-516
Look for Wall 18323 or Locus 18323
Update 18323 with Locus 18323
Look for Wall 9657 or Locus 9657
Update 9657 with Locus 9657
Look for Wall 9814 or Locus 9814
Update 9814 with Locus 9814
Look for Wall 18286 or Locus 18286
Update 18286 with Locus 18286
Look for Wall 9903 or Locus 9903
Update 9903 with Locus 9903
Look for Wall 9903 or Locus 9903
Update 9903 with Locus 9903
Look for Wall 9899 or Locus 9899
Update 9899 with Locus 9899
Look for Wall 9328 or Locus 9328
Update 9328 with Locus 9328
Look for Wall 9752 or Locus 9752
Update 9752 with Locus 9752
Look for Wall 9305 or Locus 9305
Update 9305 with Locus 9305
Look for Wall 9305 or Locus 9305
Update 9305 with Locus 9305
Look for Wall 18293 or Locus 18293
Update 18293 with Locus 18293
Look for Wall 18286 or Locus 18286
Update 18286 with Locus 18286
Look for Wall 18229 or Locus 18229
Update 18229 with Wall 18229
Look for Wall 18313 or Locus 18313
Update 18313 with Locus 18313
Look for Wall 9297 or Locus 9297
Update 9297 with Locus 9297
Look for Wall 9179 or Locus 9179
Update 9179 with Locus 9179
Look for Wall 9759 or Locus 9759
Update 9759 with Locus 9759
Look for Wall 9860 or Locus 9860
Update 9860 with Locus 9860
Look for Wall 9300 or Locus 9300
Update 9300 with Locus 9300
Look for Wall 9537 or Locus 9537
Update 9537 with Locus 9537
Look for Wall 9259 or Locus 9259
Update 9259 with Locus 9259
Look for Wall 9259 or Locus 9259
Update 9259 with Locus 9259
Look for Wall 9678 or Locus 9678
Update 9678 with Locus 9678
Look for Wall 9878 or Locus 9878
Update 9878 with Locus 9878
Look for Wall 9730 or Locus 9730
Update 9730 with Locus 9730
Look for Wall 9814 or Locus 9814
Update 9814 with Locus 9814
Look for Wall 9875 or Locus 9875
Update 9875 with Locus 9875
Look for Wall 9251 or Locus 9251
Update 9251 with Locus 9251
Look for Wall 9249 or Locus 9249
Update 9249 with Locus 9249
Look for Wall 18313 or Locus 18313
Update 18313 with Locus 18313
Look for Wall 9657 or Locus 9657
Update 9657 with Locus 9657
Look for Wall 9605 or Locus 9605
Update 9605 with Locus 9605
Look for Wall 18494 or Locus 18494
Update 18494 with Locus 18494
Look for Wall 18561 or Locus 18561
Update 18561 with Locus 18561
Look for Wall 18392 or Locus 18392
Update 18392 with Locus 18392
Look for Wall 18483 or Locus 18483
Update 18483 with Locus 18483

In [2]:

    

f_df.head(3)


    

    
Out[2]:







  

    

      

      
File ID
      
Illustration
      
Chp
      
Part Number
      
Caption
      
DB ID
      
FileName
      
FileType
      
Error in print
    
  
  

    

      
0
      
Figure 1.1
      
Figure
      
1.0
      
1
      
Fig. 1.1. Map of Tel Dor showing Area G in rel...
      
d09Z1-1001
      
d09Z1-1001.tif
      
tif
      
NaN
    
    

      
1
      
Figure 1.2
      
Figure
      
1.0
      
2
      
Fig. 1.2. A reconstruction of the Roman street...
      
d09Z1-1002
      
d09Z1-1002.tif
      
tif
      
NaN
    
    

      
2
      
Figure 1.3
      
Figure
      
1.0
      
3
      
Fig. 1.3. Area G during the first season in 19...
      
p08Z3-1365
      
p08Z3-1365.tif
      
tif
      
NaN
    
  

In [3]:

    

l_df.head(3)


    

    
Out[3]:







  

    

      

      
Region
      
Site
      
Area
      
Note
      
Locus ID
      
Original Sort Order
      
Locus/Wall
      
Number
      
Square
      
Phase
      
Contextual Integrity (I) Code
      
Contextual Integrity (I)
      
Phasing of Contents (PoC)
      
Comments
      
Context
      
Chapter
      
Status
    
  
  

    

      
0
      
Israel
      
Tel Dor
      
AI–AK:31–32
      
To facilitate navigation, Open Context editors...
      
Locus 9000
      
1
      
Locus
      
9000
      
AI–AK/31–32
      
1a
      
--
      
--
      
⪰1
      
Topsoil on top of ashlar pavement of Phase 1a ...
      
--
      
Dor IIIA: 5, 7, 8, 9, 11, 12, 13, 16
      
Not Final
    
    

      
1
      
Israel
      
Tel Dor
      
AJ:30–34
      
To facilitate navigation, Open Context editors...
      
Locus 9001
      
2
      
Locus
      
9001
      
AJ/32
      
1a
      
--
      
--
      
⪰1
      
Topsoil down to fragment of F9000
      
--
      
Dor IIIA: 12
      
Not Final
    
    

      
2
      
Israel
      
Tel Dor
      
AJ:30–34
      
To facilitate navigation, Open Context editors...
      
Locus 9002
      
3
      
Locus
      
9002
      
AJ/33
      
--
      
n
      
non-stratified
      
--
      
Topsoil
      
--
      
Dor IIIA: 13
      
Not Final
    
  

In [4]:

    

# Find matching Loci (including Wall Loci) by matching their IDs
# with text in the file metadata 'Caption' column.
for locus_wall_id in l_df['Locus ID'].unique().tolist():
    l_w_id = locus_wall_id.replace('Locus ', 'L').replace('Wall ', 'W')
    
    # l_w_mum_id is for locus or wall IDs that are long unlikely to be
    # a false positive, and lack a "L" or "W" in the caption.
    l_w_num_id = l_w_id.replace('L', ' ').replace('W', ' ')
    if len(l_w_num_id) >= 6:
        # Catch cases where the Locus / Wall ID is long like 
        # '18347'.
        l_w_indx = (
            f_df['Caption'].str.contains(l_w_id)
            | f_df['Caption'].str.contains(l_w_num_id)
        )
    else:
        # The locus / wall id is too short to trust without a 
        # "L" or "W" prefix.
        l_w_indx = f_df['Caption'].str.contains(l_w_id)
    
    if f_df[l_w_indx].empty:
        # We didn't find a match, so continue.
        continue
    print('Found: {} for {} as {}'.format(
            len(f_df[l_w_indx]), 
            locus_wall_id,
            l_w_id,
        )
    )
    file_ids = f_df[l_w_indx]['File ID'].unique().tolist()
    file_locus_data = add_to_file_context_data(
        file_ids, 
        locus_wall_id, 
        file_locus_data
    )

# Now make a dataframe of the file - locus associations
file_locus_df = pd.DataFrame(data=file_locus_data)
print('File and Locus Associations (Found: {})'.format(
    len(file_locus_df.index))
)


    

    




Found: 3 for Wall 9003 as W9003
Found: 1 for Wall 9015 as W9015
Found: 1 for Wall 9019 as W9019
Found: 2 for Locus 9025 as L9025
Found: 1 for Wall 9041 as W9041
Found: 1 for Wall 9047 as W9047
Found: 2 for Locus 9048 as L9048
Found: 3 for Wall 9058 as W9058
Found: 5 for Wall 9065 as W9065
Found: 14 for Wall 9066 as W9066
Found: 3 for Wall 9096 as W9096






    




c:\python-3-7-4\lib\site-packages\pandas\core\strings.py:1843: UserWarning: This pattern has match groups. To actually get the groups, use str.extract.
  return func(self, *args, **kwargs)






    




Found: 4 for Wall 9147 as W9147
Found: 2 for Wall 9162 as W9162
Found: 3 for Locus 9168 as L9168
Found: 2 for Wall 9180 as W9180
Found: 1 for Locus 9185 as L9185
Found: 1 for Locus 9202 as L9202
Found: 2 for Locus 9204 as L9204
Found: 21 for Wall 9211 as W9211
Found: 2 for Wall 9212 as W9212
Found: 6 for Wall 9216 as W9216
Found: 2 for Wall 9217 as W9217
Found: 1 for Wall 9243 as W9243
Found: 2 for Locus 9251 as L9251
Found: 1 for Wall 9253 as W9253
Found: 30 for Wall 9262 as W9262
Found: 30 for Wall 9266 as W9266
Found: 1 for Wall 9274 as W9274
Found: 1 for Wall 9275a–b as W9275a–b
Found: 7 for Wall 9278 as W9278
Found: 1 for Wall 9279 as W9279
Found: 10 for Wall 9282 as W9282
Found: 1 for Wall 9290 as W9290
Found: 1 for Locus 9298 as L9298
Found: 1 for Wall 9301b as W9301b
Found: 2 for Locus 9326 as L9326
Found: 1 for Wall 9340 as W9340
Found: 1 for Locus 9346 as L9346
Found: 7 for Wall 9400 as W9400
Found: 4 for Wall 9408a as W9408a
Found: 7 for Wall 9408b as W9408b
Found: 1 for Wall 9412 as W9412
Found: 3 for Wall 9413 as W9413
Found: 1 for Locus 9434 as L9434
Found: 1 for Wall 9466 as W9466
Found: 1 for Wall 9490 as W9490
Found: 1 for Wall 9491 as W9491
Found: 4 for Wall 9510 as W9510
Found: 1 for Locus 9550 as L9550
Found: 1 for Locus 9558 as L9558
Found: 1 for Wall 9560 as W9560
Found: 14 for Wall 9626 as W9626
Found: 1 for Locus 9630 as L9630
Found: 6 for Wall 9636 as W9636
Found: 4 for Locus 9658 as L9658
Found: 1 for Locus 9660 as L9660
Found: 1 for Locus 9669 as L9669
Found: 3 for Wall 9675 as W9675
Found: 1 for Locus 9679 as L9679
Found: 1 for Locus 9680 as L9680
Found: 19 for Wall 9684 as W9684
Found: 1 for Locus 9698 as L9698
Found: 3 for Wall 9702 as W9702
Found: 13 for Wall 9704 as W9704
Found: 1 for Locus 9714 as L9714
Found: 6 for Wall 9715 as W9715
Found: 13 for Wall 9728 as W9728
Found: 15 for Wall 9729 as W9729
Found: 6 for Wall 9735 as W9735
Found: 1 for Locus 9736 as L9736
Found: 1 for Locus 9752 as L9752
Found: 1 for Locus 9762 as L9762
Found: 1 for Locus 9766 as L9766
Found: 1 for Locus 9779 as L9779
Found: 4 for Wall 9800 as W9800
Found: 2 for Locus 9805 as L9805
Found: 1 for Locus 9816 as L9816
Found: 4 for Wall 9825 as W9825
Found: 3 for Wall 9841 as W9841
Found: 1 for Wall 9845 as W9845
Found: 1 for Locus 9865 as L9865
Found: 2 for Locus 9871 as L9871
Found: 1 for Locus 9875 as L9875
Found: 7 for Locus 9880 as L9880
Found: 2 for Locus 9882 as L9882
Found: 2 for Wall 9885 as W9885
Found: 5 for Wall 9887 as W9887
Found: 2 for Locus 9890 as L9890
Found: 1 for Locus 9895 as L9895
Found: 1 for Locus 9903 as L9903
Found: 2 for Wall 9904 as W9904
Found: 9 for Wall 9909 as W9909
Found: 8 for Wall 9914 as W9914
Found: 14 for Wall 9915 as W9915
Found: 1 for Wall 9917 as W9917
Found: 5 for Wall 9936 as W9936
Found: 1 for Wall 9942 as W9942
Found: 1 for Wall 9943 as W9943
Found: 2 for Wall 9952 as W9952
Found: 11 for Wall 9957 as W9957
Found: 2 for Wall 9959 as W9959
Found: 3 for Wall 9961 as W9961
Found: 6 for Wall 9963 as W9963
Found: 5 for Wall 9964 as W9964
Found: 1 for Locus 9965 as L9965
Found: 1 for Wall 9970 as W9970
Found: 1 for Locus 9974 as L9974
Found: 2 for Wall 9975 as W9975
Found: 9 for Locus 9982 as L9982
Found: 1 for Locus 9985 as L9985
Found: 4 for Wall 9989 as W9989
Found: 8 for Wall 9990 as W9990
Found: 3 for Wall 9993 as W9993
Found: 1 for Wall 9998 as W9998
Found: 1 for Locus 18000 as L18000
Found: 3 for Wall 18010a as W18010a
Found: 1 for Locus 18030 as L18030
Found: 9 for Locus 18033 as L18033
Found: 1 for Locus 18034 as L18034
Found: 1 for Locus 18035 as L18035
Found: 1 for Locus 18036 as L18036
Found: 1 for Locus 18041 as L18041
Found: 12 for Wall 18045 as W18045
Found: 19 for Wall 18048 as W18048
Found: 1 for Locus 18054 as L18054
Found: 1 for Locus 18059 as L18059
Found: 1 for Locus 18065 as L18065
Found: 2 for Locus 18067 as L18067
Found: 1 for Locus 18075 as L18075
Found: 1 for Locus 18082 as L18082
Found: 1 for Locus 18088 as L18088
Found: 2 for Locus 18089 as L18089
Found: 1 for Locus 18107 as L18107
Found: 1 for Locus 18121 as L18121
Found: 1 for Locus 18137 as L18137
Found: 1 for Locus 18153 as L18153
Found: 1 for Locus 18154 as L18154
Found: 2 for Locus 18182 as L18182
Found: 1 for Locus 18199 as L18199
Found: 1 for Locus 18205 as L18205
Found: 1 for Wall 18206 as W18206
Found: 1 for Locus 18213 as L18213
Found: 1 for Locus 18216 as L18216
Found: 1 for Wall 18218 as W18218
Found: 1 for Locus 18225 as L18225
Found: 22 for Wall 18229 as W18229
Found: 1 for Locus 18239 as L18239
Found: 2 for Locus 18241 as L18241
Found: 1 for Locus 18242 as L18242
Found: 1 for Locus 18243 as L18243
Found: 1 for Wall 18248 as W18248
Found: 9 for Wall 18250 as W18250
Found: 1 for Locus 18255 as L18255
Found: 5 for Locus 18275 as L18275
Found: 3 for Locus 18286 as L18286
Found: 3 for Locus 18293 as L18293
Found: 6 for Wall 18296 as W18296
Found: 3 for Locus 18298 as L18298
Found: 1 for Wall 18300 as W18300
Found: 7 for Locus 18308 as L18308
Found: 1 for Locus 18312 as L18312
Found: 1 for Locus 18313 as L18313
Found: 7 for Wall 18315 as W18315
Found: 1 for Locus 18319 as L18319
Found: 1 for Locus 18324 as L18324
Found: 2 for Locus 18330 as L18330
Found: 9 for Locus 18333 as L18333
Found: 3 for Locus 18347 as L18347
Found: 8 for Wall 18349 as W18349
Found: 1 for Locus 18361 as L18361
Found: 2 for Locus 18363 as L18363
Found: 1 for Locus 18380 as L18380
Found: 2 for Locus 18399 as L18399
Found: 1 for Locus 18400 as L18400
Found: 2 for Wall 18463 as W18463
Found: 2 for Wall 18471 as W18471
Found: 9 for Wall 18481 as W18481
Found: 1 for Locus 18482 as L18482
Found: 2 for Wall 18503 as W18503
Found: 2 for Locus 18509 as L18509
Found: 2 for Wall 18514 as W18514
Found: 5 for Wall 18515 as W18515
Found: 2 for Wall 18516 as W18516
Found: 1 for Wall 18528 as W18528
Found: 1 for Locus 18529 as L18529
Found: 3 for Locus 18570 as L18570
Found: 2 for Wall 18575 as W18575
Found: 2 for Wall 18577 as W18577
Found: 1 for Locus 18584 as L18584
Found: 2 for Wall 18912 as W18912
Found: 1 for Locus 04G0-004 as L04G0-004
Found: 1 for Wall 04G0-008 as W04G0-008
File and Locus Associations (Found: 680)

In [5]:

    

# Find matching Loci (including Wall Loci) by matching their Squares
# with text in the file metadata 'Caption' column.
l_df_sq = l_df[~l_df['Square'].isnull()]
for square in l_df_sq['Square'].astype(str).unique().tolist():
    sq_indx = f_df['Caption'].str.contains(square)
    if len(square) < 3 or f_df[sq_indx].empty:
        # Not enough characters for secure match.
        continue
    # Get all file_ids that have his square in their captions
    file_ids = f_df[sq_indx]['File ID'].unique().tolist()
    # Get all the locus ids that are associated with this square
    area_ids = l_df[
        l_df['Square']==square
    ]['Area'].unique().tolist()
    print('Found: {} files with square {} and {} areas'.format(
            len(f_df[sq_indx]), 
            square,
            len(area_ids)
        )
    )
    # Now add to the file_locus_data.
    file_square_data = add_to_file_context_data(
        file_ids, 
        area_ids, 
        file_square_data,
        context_id_col='Area'
    )

# Now make a dataframe of the file - area associations
file_area_df = pd.DataFrame(data=file_square_data)
print('File and Area Associations (Found: {})'.format(
    len(file_area_df.index))
)


    

    




Found: 22 files with square AJ/32 and 1 areas
Found: 14 files with square AJ/33 and 1 areas
Found: 3 files with square AJ–AK/33 and 1 areas
Found: 22 files with square AI/32 and 1 areas
Found: 1 files with square AJ/31 and 1 areas
Found: 20 files with square AI/31 and 1 areas
Found: 1 files with square AI/31–32 and 1 areas
Found: 1 files with square AI/31–33 and 1 areas
Found: 4 files with square AJ/32–33 and 1 areas
Found: 12 files with square AK/32 and 1 areas
Found: 6 files with square AJ/34 and 1 areas
Found: 26 files with square AI/33 and 1 areas
Found: 9 files with square AJ–AK/32 and 1 areas
Found: 1 files with square AI/34 and 1 areas
Found: 6 files with square AH/33 and 1 areas
Found: 5 files with square AK/33 and 1 areas
Found: 2 files with square AK/34 and 1 areas
Found: 4 files with square AH/34 and 1 areas
Found: 3 files with square AI–AJ/32 and 1 areas
Found: 1 files with square AI–AJ/33 and 1 areas
Found: 8 files with square AH–AI/33 and 1 areas
Found: 1 files with square AI/33–34 and 1 areas
Found: 1 files with square AG/34 and 1 areas
Found: 11 files with square AG/33 and 1 areas
Found: 1 files with square AK/32–33 and 1 areas
Found: 2 files with square AG/33–34 and 1 areas
Found: 1 files with square AI–AJ/32–33 and 1 areas
File and Area Associations (Found: 188)

In [6]:

    

context_df = pd.merge(file_locus_df, file_area_df, on='File ID', how='outer')
context_linked_files = context_df['File ID'].unique().tolist()
print('Found File and Context Associations for {} unique files (total rows: {})'.format(
    len(context_linked_files),
    len(context_df.index))
)


# Get a list of files that do NOT have context associations
no_context_files = f_df[
    ~f_df['File ID'].isin(context_linked_files)
]['File ID'].unique().tolist()

file_site_data = {
    'File ID':[], 
    'Site Area': [],
}
file_site_data = add_to_file_context_data(
    no_context_files, 
    'Area G', 
    file_site_data,
    context_id_col='Site Area'
)
site_df = pd.DataFrame(data=file_site_data)
context_df = pd.concat([context_df, site_df], sort=False)

# Set the column order for nice aesthetics
context_df = context_df[['File ID', 'Site Area', 'Area', 'Locus ID']]
context_df.sort_values(by=['File ID', 'Locus ID', 'Area'], inplace=True)

context_df.to_csv(path_files_contexts, index=False)
context_df.head(3)


    

    




Found File and Context Associations for 426 unique files (total rows: 857)






    
Out[6]:







  

    

      

      
File ID
      
Site Area
      
Area
      
Locus ID
    
  
  

    

      
0
      
Figure 1.1
      
Area G
      
NaN
      
NaN
    
    

      
532
      
Figure 1.10
      
NaN
      
AJ:30–34
      
Wall 9914
    
    

      
733
      
Figure 1.11
      
NaN
      
AI–AJ:32–34
      
NaN