Markdown preview - Polars dataframes#
itables.to_markdown_table() returns the Markdown table that itables.show()
prints when it can’t display an interactive table at all - see
Markdown preview for why, and when, this is
shown. This page shows it for each of our test Polars
dataframes; see Polars dataframes for the same
dataframes rendered as interactive tables.
import itables
dict_of_test_dfs = itables.sample_polars_dfs.get_dict_of_test_dfs()
empty#
print(itables.to_markdown_table(dict_of_test_dfs["empty"]))
| |
| |
No rows#
print(itables.to_markdown_table(dict_of_test_dfs["no_rows"]))
| a |
| - |
bool#
print(itables.to_markdown_table(dict_of_test_dfs["bool"]))
| a | b | c | d |
| ---- | ----- | ----- | ----- |
| True | True | False | False |
| True | False | True | False |
Nullable boolean#
print(itables.to_markdown_table(dict_of_test_dfs["nullable_boolean"]))
| a | b | c | d |
| ---- | ----- | ----- | ----- |
| True | True | False | |
| True | False | | False |
| | False | True | False |
int#
print(itables.to_markdown_table(dict_of_test_dfs["int"]))
| a | b | c | d | e |
| -- | -- | -- | -- | -- |
| -1 | 2 | -3 | 4 | -5 |
| 6 | -7 | 8 | -9 | 10 |
Nullable integer#
print(itables.to_markdown_table(dict_of_test_dfs["nullable_int"]))
| a | b | c |
| -- | -- | -- |
| -1 | 2 | -3 |
| 4 | -5 | 6 |
| | 7 | |
float#
print(itables.to_markdown_table(dict_of_test_dfs["float"]))
| int | inf | nan | math | unsorted |
| --- | ---- | --- | -------- | -------- |
| 0.0 | inf | NaN | 3.141593 | 100.0 |
| 1.0 | -inf | NaN | 2.718282 | NaN |
| 2.0 | inf | NaN | 3.141593 | NaN |
| 3.0 | -inf | NaN | 2.718282 | 20.0 |
| 4.0 | inf | NaN | 3.141593 | 3.141593 |
| 5.0 | -inf | NaN | 2.718282 | 2.718282 |
| 6.0 | inf | NaN | 3.141593 | 0.0 |
| 7.0 | -inf | NaN | 2.718282 | -0.0 |
| 8.0 | inf | NaN | 3.141593 | inf |
| 9.0 | -inf | NaN | 2.718282 | -inf |
float_types#
print(itables.to_markdown_table(dict_of_test_dfs["float_types"]))
| float16 | float32 | float64 | decimal |
| -------- | -------- | -------- | -------- |
| 1.0 | 1.0 | 1.0 | 1.000000 |
| 0.0 | 0.0 | 0.0 | 0.000000 |
| 3.140625 | 3.141593 | 3.141593 | 3.000000 |
| NaN | NaN | NaN | null |
| inf | inf | inf | null |
| -inf | -inf | -inf | null |
str#
print(itables.to_markdown_table(dict_of_test_dfs["str"]))
| text_column | very_long_text_column |
| ----------- | ----------------------------------------------------------------------- |
| some | a very very very very very very very very very very very very long text |
| text | a very very very very very very very very very very very very long text |
time#
print(itables.to_markdown_table(dict_of_test_dfs["time"]))
| datetime | timestamp | timedelta |
| ------------------- | -------------------------- | --------- |
| 2000-01-01 00:00:00 | null | 2d |
| 2001-01-01 00:00:00 | 2000-01-01 18:55:33 | 50s |
| null | 2001-01-01 18:55:55.456654 | null |
date_range#
print(itables.to_markdown_table(dict_of_test_dfs["date_range"]))
| timestamps |
| -------------------------- |
| 2026-07-19 22:58:10.737395 |
| 2026-07-19 22:58:11.737395 |
| 2026-07-19 22:58:12.737395 |
| 2026-07-19 22:58:13.737395 |
| 2026-07-19 22:58:14.737395 |
ordered_categories#
print(itables.to_markdown_table(dict_of_test_dfs["ordered_categories"]))
| int | category |
| --- | -------- |
| 0 | first |
| 1 | second |
| 2 | third |
| 3 | fourth |
object#
print(itables.to_markdown_table(dict_of_test_dfs["object"]))
| dict | list |
| ------ | ---------- |
| {1} | ["a"] |
| {null} | ["1", "2"] |
countries#
print(itables.to_markdown_table(dict_of_test_dfs["countries"]))
| iso2Code | region | country | capital | longitude | latitude |
| -------- | -------------------------- | -------------------- | ---------------- | --------- | -------- |
| AW | Latin America & Caribbean | Aruba | Oranjestad | -70.0167 | 12.5167 |
| AF | South Asia | Afghanistan | Kabul | 69.1761 | 34.5228 |
| AO | Sub-Saharan Africa | Angola | Luanda | 13.242 | -8.81155 |
| AL | Europe & Central Asia | Albania | Tirane | 19.8172 | 41.3317 |
| AD | Europe & Central Asia | Andorra | Andorra la Vella | 1.5218 | 42.5075 |
| AE | Middle East & North Africa | United Arab Emirates | Abu Dhabi | 54.3705 | 24.4764 |
| AR | Latin America & Caribbean | Argentina | Buenos Aires | -58.4173 | -34.6118 |
| AM | Europe & Central Asia | Armenia | Yerevan | 44.509 | 40.1596 |
| AS | East Asia & Pacific | American Samoa | Pago Pago | -170.691 | -14.2846 |
| AG | Latin America & Caribbean | Antigua and Barbuda | Saint John's | -61.8456 | 17.1175 |
*(198 more rows not shown)*
int_float_str#
print(itables.to_markdown_table(dict_of_test_dfs["int_float_str"]))
| int | float | str |
| --- | ----- | --- |
| 0 | 0.5 | a |
| 1 | 1.5 | b |
| 2 | 2.5 | c |
| 3 | 3.5 | d |
| 4 | 4.5 | e |
| 5 | 5.5 | f |
| 6 | 6.5 | g |
| 7 | 7.5 | h |
| 8 | 8.5 | i |
| 9 | 9.5 | j |
*(90 more rows not shown)*
wide#
print(itables.to_markdown_table(dict_of_test_dfs["wide"]))
| column_0 | column_1 | column_2 | column_3 | column_4 | column_5 | column_6 | column_7 | column_8 | column_9 | column_10 | column_11 | column_12 | column_13 | column_14 | column_15 | column_16 | column_17 | column_18 | column_19 | column_20 | column_21 | column_22 | column_23 | column_24 | column_25 | column_26 | column_27 | column_28 | column_29 | column_30 | column_31 | column_32 | column_33 | column_34 | column_35 | column_36 | column_37 | column_38 | column_39 | column_40 | column_41 | column_42 | column_43 | column_44 | column_55 | column_56 | column_57 | column_58 | column_59 | column_60 | column_61 | column_62 | column_63 | column_64 | column_65 | column_66 | column_67 | column_68 | column_69 | column_70 | column_71 | column_72 | column_73 | column_74 | column_75 | column_76 | column_77 | column_78 | column_79 | column_80 | column_81 | column_82 | column_83 | column_84 | column_85 | column_86 | column_87 | column_88 | column_89 | column_90 | column_91 | column_92 | column_93 | column_94 | column_95 | column_96 | column_97 | column_98 | column_99 |
| -------- | -------- | -------- | -------- | -------- | -------- | -------- | -------- | -------- | -------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- |
| 0.0 | 0.01 | 0.02 | 0.03 | 0.04 | 0.05 | 0.06 | 0.07 | 0.08 | 0.09 | 0.1 | 0.11 | 0.12 | 0.13 | 0.14 | 0.15 | 0.16 | 0.17 | 0.18 | 0.19 | 0.2 | 0.21 | 0.22 | 0.23 | 0.24 | 0.25 | 0.26 | 0.27 | 0.28 | 0.29 | 0.3 | 0.31 | 0.32 | 0.33 | 0.34 | 0.35 | 0.36 | 0.37 | 0.38 | 0.39 | 0.4 | 0.41 | 0.42 | 0.43 | 0.44 | 0.55 | 0.56 | 0.57 | 0.58 | 0.59 | 0.6 | 0.61 | 0.62 | 0.63 | 0.64 | 0.65 | 0.66 | 0.67 | 0.68 | 0.69 | 0.7 | 0.71 | 0.72 | 0.73 | 0.74 | 0.75 | 0.76 | 0.77 | 0.78 | 0.79 | 0.8 | 0.81 | 0.82 | 0.83 | 0.84 | 0.85 | 0.86 | 0.87 | 0.88 | 0.89 | 0.9 | 0.91 | 0.92 | 0.93 | 0.94 | 0.95 | 0.96 | 0.97 | 0.98 | 0.99 |
| 0.0001 | 0.0101 | 0.0201 | 0.0301 | 0.0401 | 0.0501 | 0.0601 | 0.0701 | 0.0801 | 0.0901 | 0.1001 | 0.1101 | 0.1201 | 0.1301 | 0.1401 | 0.1501 | 0.1601 | 0.1701 | 0.1801 | 0.1901 | 0.2001 | 0.2101 | 0.2201 | 0.2301 | 0.2401 | 0.2501 | 0.2601 | 0.2701 | 0.2801 | 0.2901 | 0.3001 | 0.3101 | 0.3201 | 0.3301 | 0.3401 | 0.3501 | 0.3601 | 0.3701 | 0.3801 | 0.3901 | 0.4001 | 0.4101 | 0.4201 | 0.4301 | 0.4401 | 0.5501 | 0.5601 | 0.5701 | 0.5801 | 0.5901 | 0.6001 | 0.6101 | 0.6201 | 0.6301 | 0.6401 | 0.6501 | 0.6601 | 0.6701 | 0.6801 | 0.6901 | 0.7001 | 0.7101 | 0.7201 | 0.7301 | 0.7401 | 0.7501 | 0.7601 | 0.7701 | 0.7801 | 0.7901 | 0.8001 | 0.8101 | 0.8201 | 0.8301 | 0.8401 | 0.8501 | 0.8601 | 0.8701 | 0.8801 | 0.8901 | 0.9001 | 0.9101 | 0.9201 | 0.9301 | 0.9401 | 0.9501 | 0.9601 | 0.9701 | 0.9801 | 0.9901 |
| 0.0002 | 0.0102 | 0.0202 | 0.0302 | 0.0402 | 0.0502 | 0.0602 | 0.0702 | 0.0802 | 0.0902 | 0.1002 | 0.1102 | 0.1202 | 0.1302 | 0.1402 | 0.1502 | 0.1602 | 0.1702 | 0.1802 | 0.1902 | 0.2002 | 0.2102 | 0.2202 | 0.2302 | 0.2402 | 0.2502 | 0.2602 | 0.2702 | 0.2802 | 0.2902 | 0.3002 | 0.3102 | 0.3202 | 0.3302 | 0.3402 | 0.3502 | 0.3602 | 0.3702 | 0.3802 | 0.3902 | 0.4002 | 0.4102 | 0.4202 | 0.4302 | 0.4402 | 0.5502 | 0.5602 | 0.5702 | 0.5802 | 0.5902 | 0.6002 | 0.6102 | 0.6202 | 0.6302 | 0.6402 | 0.6502 | 0.6602 | 0.6702 | 0.6802 | 0.6902 | 0.7002 | 0.7102 | 0.7202 | 0.7302 | 0.7402 | 0.7502 | 0.7602 | 0.7702 | 0.7802 | 0.7902 | 0.8002 | 0.8102 | 0.8202 | 0.8302 | 0.8402 | 0.8502 | 0.8602 | 0.8702 | 0.8802 | 0.8902 | 0.9002 | 0.9102 | 0.9202 | 0.9302 | 0.9402 | 0.9502 | 0.9602 | 0.9702 | 0.9802 | 0.9902 |
| 0.0003 | 0.0103 | 0.0203 | 0.0303 | 0.0403 | 0.0503 | 0.0603 | 0.0703 | 0.0803 | 0.0903 | 0.1003 | 0.1103 | 0.1203 | 0.1303 | 0.1403 | 0.1503 | 0.1603 | 0.1703 | 0.1803 | 0.1903 | 0.2003 | 0.2103 | 0.2203 | 0.2303 | 0.2403 | 0.2503 | 0.2603 | 0.2703 | 0.2803 | 0.2903 | 0.3003 | 0.3103 | 0.3203 | 0.3303 | 0.3403 | 0.3503 | 0.3603 | 0.3703 | 0.3803 | 0.3903 | 0.4003 | 0.4103 | 0.4203 | 0.4303 | 0.4403 | 0.5503 | 0.5603 | 0.5703 | 0.5803 | 0.5903 | 0.6003 | 0.6103 | 0.6203 | 0.6303 | 0.6403 | 0.6503 | 0.6603 | 0.6703 | 0.6803 | 0.6903 | 0.7003 | 0.7103 | 0.7203 | 0.7303 | 0.7403 | 0.7503 | 0.7603 | 0.7703 | 0.7803 | 0.7903 | 0.8003 | 0.8103 | 0.8203 | 0.8303 | 0.8403 | 0.8503 | 0.8603 | 0.8703 | 0.8803 | 0.8903 | 0.9003 | 0.9103 | 0.9203 | 0.9303 | 0.9403 | 0.9503 | 0.9603 | 0.9703 | 0.9803 | 0.9903 |
| 0.0004 | 0.0104 | 0.0204 | 0.0304 | 0.0404 | 0.0504 | 0.0604 | 0.0704 | 0.0804 | 0.0904 | 0.1004 | 0.1104 | 0.1204 | 0.1304 | 0.1404 | 0.1504 | 0.1604 | 0.1704 | 0.1804 | 0.1904 | 0.2004 | 0.2104 | 0.2204 | 0.2304 | 0.2404 | 0.2504 | 0.2604 | 0.2704 | 0.2804 | 0.2904 | 0.3004 | 0.3104 | 0.3204 | 0.3304 | 0.3404 | 0.3504 | 0.3604 | 0.3704 | 0.3804 | 0.3904 | 0.4004 | 0.4104 | 0.4204 | 0.4304 | 0.4404 | 0.5504 | 0.5604 | 0.5704 | 0.5804 | 0.5904 | 0.6004 | 0.6104 | 0.6204 | 0.6304 | 0.6404 | 0.6504 | 0.6604 | 0.6704 | 0.6804 | 0.6904 | 0.7004 | 0.7104 | 0.7204 | 0.7304 | 0.7404 | 0.7504 | 0.7604 | 0.7704 | 0.7804 | 0.7904 | 0.8004 | 0.8104 | 0.8204 | 0.8304 | 0.8404 | 0.8504 | 0.8604 | 0.8704 | 0.8804 | 0.8904 | 0.9004 | 0.9104 | 0.9204 | 0.9304 | 0.9404 | 0.9504 | 0.9604 | 0.9704 | 0.9804 | 0.9904 |
| 0.0005 | 0.0105 | 0.0205 | 0.0305 | 0.0405 | 0.0505 | 0.0605 | 0.0705 | 0.0805 | 0.0905 | 0.1005 | 0.1105 | 0.1205 | 0.1305 | 0.1405 | 0.1505 | 0.1605 | 0.1705 | 0.1805 | 0.1905 | 0.2005 | 0.2105 | 0.2205 | 0.2305 | 0.2405 | 0.2505 | 0.2605 | 0.2705 | 0.2805 | 0.2905 | 0.3005 | 0.3105 | 0.3205 | 0.3305 | 0.3405 | 0.3505 | 0.3605 | 0.3705 | 0.3805 | 0.3905 | 0.4005 | 0.4105 | 0.4205 | 0.4305 | 0.4405 | 0.5505 | 0.5605 | 0.5705 | 0.5805 | 0.5905 | 0.6005 | 0.6105 | 0.6205 | 0.6305 | 0.6405 | 0.6505 | 0.6605 | 0.6705 | 0.6805 | 0.6905 | 0.7005 | 0.7105 | 0.7205 | 0.7305 | 0.7405 | 0.7505 | 0.7605 | 0.7705 | 0.7805 | 0.7905 | 0.8005 | 0.8105 | 0.8205 | 0.8305 | 0.8405 | 0.8505 | 0.8605 | 0.8705 | 0.8805 | 0.8905 | 0.9005 | 0.9105 | 0.9205 | 0.9305 | 0.9405 | 0.9505 | 0.9605 | 0.9705 | 0.9805 | 0.9905 |
| 0.0006 | 0.0106 | 0.0206 | 0.0306 | 0.0406 | 0.0506 | 0.0606 | 0.0706 | 0.0806 | 0.0906 | 0.1006 | 0.1106 | 0.1206 | 0.1306 | 0.1406 | 0.1506 | 0.1606 | 0.1706 | 0.1806 | 0.1906 | 0.2006 | 0.2106 | 0.2206 | 0.2306 | 0.2406 | 0.2506 | 0.2606 | 0.2706 | 0.2806 | 0.2906 | 0.3006 | 0.3106 | 0.3206 | 0.3306 | 0.3406 | 0.3506 | 0.3606 | 0.3706 | 0.3806 | 0.3906 | 0.4006 | 0.4106 | 0.4206 | 0.4306 | 0.4406 | 0.5506 | 0.5606 | 0.5706 | 0.5806 | 0.5906 | 0.6006 | 0.6106 | 0.6206 | 0.6306 | 0.6406 | 0.6506 | 0.6606 | 0.6706 | 0.6806 | 0.6906 | 0.7006 | 0.7106 | 0.7206 | 0.7306 | 0.7406 | 0.7506 | 0.7606 | 0.7706 | 0.7806 | 0.7906 | 0.8006 | 0.8106 | 0.8206 | 0.8306 | 0.8406 | 0.8506 | 0.8606 | 0.8706 | 0.8806 | 0.8906 | 0.9006 | 0.9106 | 0.9206 | 0.9306 | 0.9406 | 0.9506 | 0.9606 | 0.9706 | 0.9806 | 0.9906 |
| 0.0007 | 0.0107 | 0.0207 | 0.0307 | 0.0407 | 0.0507 | 0.0607 | 0.0707 | 0.0807 | 0.0907 | 0.1007 | 0.1107 | 0.1207 | 0.1307 | 0.1407 | 0.1507 | 0.1607 | 0.1707 | 0.1807 | 0.1907 | 0.2007 | 0.2107 | 0.2207 | 0.2307 | 0.2407 | 0.2507 | 0.2607 | 0.2707 | 0.2807 | 0.2907 | 0.3007 | 0.3107 | 0.3207 | 0.3307 | 0.3407 | 0.3507 | 0.3607 | 0.3707 | 0.3807 | 0.3907 | 0.4007 | 0.4107 | 0.4207 | 0.4307 | 0.4407 | 0.5507 | 0.5607 | 0.5707 | 0.5807 | 0.5907 | 0.6007 | 0.6107 | 0.6207 | 0.6307 | 0.6407 | 0.6507 | 0.6607 | 0.6707 | 0.6807 | 0.6907 | 0.7007 | 0.7107 | 0.7207 | 0.7307 | 0.7407 | 0.7507 | 0.7607 | 0.7707 | 0.7807 | 0.7907 | 0.8007 | 0.8107 | 0.8207 | 0.8307 | 0.8407 | 0.8507 | 0.8607 | 0.8707 | 0.8807 | 0.8907 | 0.9007 | 0.9107 | 0.9207 | 0.9307 | 0.9407 | 0.9507 | 0.9607 | 0.9707 | 0.9807 | 0.9907 |
| 0.0008 | 0.0108 | 0.0208 | 0.0308 | 0.0408 | 0.0508 | 0.0608 | 0.0708 | 0.0808 | 0.0908 | 0.1008 | 0.1108 | 0.1208 | 0.1308 | 0.1408 | 0.1508 | 0.1608 | 0.1708 | 0.1808 | 0.1908 | 0.2008 | 0.2108 | 0.2208 | 0.2308 | 0.2408 | 0.2508 | 0.2608 | 0.2708 | 0.2808 | 0.2908 | 0.3008 | 0.3108 | 0.3208 | 0.3308 | 0.3408 | 0.3508 | 0.3608 | 0.3708 | 0.3808 | 0.3908 | 0.4008 | 0.4108 | 0.4208 | 0.4308 | 0.4408 | 0.5508 | 0.5608 | 0.5708 | 0.5808 | 0.5908 | 0.6008 | 0.6108 | 0.6208 | 0.6308 | 0.6408 | 0.6508 | 0.6608 | 0.6708 | 0.6808 | 0.6908 | 0.7008 | 0.7108 | 0.7208 | 0.7308 | 0.7408 | 0.7508 | 0.7608 | 0.7708 | 0.7808 | 0.7908 | 0.8008 | 0.8108 | 0.8208 | 0.8308 | 0.8408 | 0.8508 | 0.8608 | 0.8708 | 0.8808 | 0.8908 | 0.9008 | 0.9108 | 0.9208 | 0.9308 | 0.9408 | 0.9508 | 0.9608 | 0.9708 | 0.9808 | 0.9908 |
| 0.0009 | 0.0109 | 0.0209 | 0.0309 | 0.0409 | 0.0509 | 0.0609 | 0.0709 | 0.0809 | 0.0909 | 0.1009 | 0.1109 | 0.1209 | 0.1309 | 0.1409 | 0.1509 | 0.1609 | 0.1709 | 0.1809 | 0.1909 | 0.2009 | 0.2109 | 0.2209 | 0.2309 | 0.2409 | 0.2509 | 0.2609 | 0.2709 | 0.2809 | 0.2909 | 0.3009 | 0.3109 | 0.3209 | 0.3309 | 0.3409 | 0.3509 | 0.3609 | 0.3709 | 0.3809 | 0.3909 | 0.4009 | 0.4109 | 0.4209 | 0.4309 | 0.4409 | 0.5509 | 0.5609 | 0.5709 | 0.5809 | 0.5909 | 0.6009 | 0.6109 | 0.6209 | 0.6309 | 0.6409 | 0.6509 | 0.6609 | 0.6709 | 0.6809 | 0.6909 | 0.7009 | 0.7109 | 0.7209 | 0.7309 | 0.7409 | 0.7509 | 0.7609 | 0.7709 | 0.7809 | 0.7909 | 0.8009 | 0.8109 | 0.8209 | 0.8309 | 0.8409 | 0.8509 | 0.8609 | 0.8709 | 0.8809 | 0.8909 | 0.9009 | 0.9109 | 0.9209 | 0.9309 | 0.9409 | 0.9509 | 0.9609 | 0.9709 | 0.9809 | 0.9909 |
*(90 more rows and 10 more columns not shown)*
long_column_names#
print(itables.to_markdown_table(dict_of_test_dfs["long_column_names"]))
| short name | very very very very very long name | very very very very very very very very very very long name | very very very very very very very very very very very very very very very very very very very very long name | nospaceinveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryverylongname | nospaceinveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryveryverylongname |
| ---------- | ---------------------------------- | ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| 0 | 0 | 1 | 2 | 3 | 3 |
| 0 | 0 | 1 | 2 | 3 | 3 |
| 0 | 0 | 1 | 2 | 3 | 3 |
| 0 | 0 | 1 | 2 | 3 | 3 |
| 0 | 0 | 1 | 2 | 3 | 3 |
big_integers#
print(itables.to_markdown_table(dict_of_test_dfs["big_integers"]))
| bigint | expected |
| -------------------- | -------------------- |
| -1234567890123456789 | -1234567890123456789 |
| 1234567890123456789 | 1234567890123456789 |
| 2345678901234567890 | 2345678901234567890 |
| 3456789012345678901 | 3456789012345678901 |