Plain table:
       txn_amount  originator_id  beneficiary_id    txn_date
0     3764.712235         100629          100376  1989-10-19
1    11116.175155         200041          100983  1975-06-01
2     6344.945192         100379          100741  1987-08-19
3    14507.394441         100522          100488  2015-12-17
4     2176.384742         100833          100238  2013-06-07
..            ...            ...             ...         ...
267   5218.986301         200085          100539  1971-12-27
268   3824.414095         100341          200046  1981-09-22
269   3806.414095         200046          200083  1978-03-26
270   3723.414095         200083          200046  1989-12-03
271   3656.414095         200046          100341  1997-02-06

[1076 rows x 4 columns]
Plain table with a limit hint: (loads 1 file instead of 4)
       txn_amount  originator_id  beneficiary_id    txn_date
0     3764.712235         100629          100376  1989-10-19
1    11116.175155         200041          100983  1975-06-01
2     6344.945192         100379          100741  1987-08-19
3    14507.394441         100522          100488  2015-12-17
4     2176.384742         100833          100238  2013-06-07
..            ...            ...             ...         ...
263   6836.262785         100974          100967  1977-05-14
264  11963.760413         100944          100914  1970-10-27
265   4647.319732         100302          100992  2022-01-21
266   2004.544911         100276          100551  1985-08-10
267   1284.569306         100446          100292  1990-03-15

[268 rows x 4 columns]
Dask DF partitions normally:
4
Dask DF partitions with num_partitions=2:
2
Table that has CDF and partitioning:
       txn_amount  originator_id  beneficiary_id    txn_date  century
0      300.000000         100578          100997  2022-09-13       21
0      200.000000         100578          100997  2022-09-13       21
0      100.000000         100578          100997  2022-09-13       21
0     2233.924202         100578          100997  1980-07-16       20
1    10947.263716         100759          100798  1980-12-02       20
..            ...            ...             ...         ...      ...
110  10932.747256         200084          100472  2016-01-08       21
111   5546.830723         100446          100956  2000-07-12       21
112   6547.763194         100010          100143  2007-01-30       21
113   5937.250450         100273          200068  2003-12-09       21
114   2212.082283         100854          100791  2020-06-10       21

[1079 rows x 5 columns]
Latest version:
4
Load version 2 instead:
       txn_amount  originator_id  beneficiary_id    txn_date  century
0      100.000000         100578          100997  2022-09-13       21
0     2233.924202         100578          100997  1980-07-16       20
1    10947.263716         100759          100798  1980-12-02       20
2     6734.096397         100081          200011  1988-08-17       20
3     1223.820002         100871          100855  1996-05-22       20
..            ...            ...             ...         ...      ...
110  10932.747256         200084          100472  2016-01-08       21
111   5546.830723         100446          100956  2000-07-12       21
112   6547.763194         100010          100143  2007-01-30       21
113   5937.250450         100273          200068  2003-12-09       21
114   2212.082283         100854          100791  2020-06-10       21

[1077 rows x 5 columns]
Load a specific partition via a predicate hint: (doesn't work)
       txn_amount  originator_id  beneficiary_id    txn_date  century
0      300.000000         100578          100997  2022-09-13       21
0      200.000000         100578          100997  2022-09-13       21
0      100.000000         100578          100997  2022-09-13       21
0     2233.924202         100578          100997  1980-07-16       20
1    10947.263716         100759          100798  1980-12-02       20
..            ...            ...             ...         ...      ...
110  10932.747256         200084          100472  2016-01-08       21
111   5546.830723         100446          100956  2000-07-12       21
112   6547.763194         100010          100143  2007-01-30       21
113   5937.250450         100273          200068  2003-12-09       21
114   2212.082283         100854          100791  2020-06-10       21

[1079 rows x 5 columns]
Use PyArrow filtering:
   txn_amount  originator_id  beneficiary_id    txn_date  century
0       100.0         100578          100997  2022-09-13       21
Get just some columns:
       txn_amount  beneficiary_id  century
0      300.000000          100997       21
0      200.000000          100997       21
0      100.000000          100997       21
0     2233.924202          100997       20
1    10947.263716          100798       20
..            ...             ...      ...
110  10932.747256          100472       21
111   5546.830723          100956       21
112   6547.763194          100143       21
113   5937.250450          200068       21
114   2212.082283          100791       21

[1079 rows x 3 columns]
