spa-l1-paris-amenity-within
Map (reference ← swipe → agent)
0:00
I'm putting together a neighbourhood demographic crosswalk for the INSEE census team and need each amenity tagged with the Paris arrondissement it falls inside. Can you join `amenities` to `arrondissements` and write the result to `amenity_to_arrondissement.csv` with one row per amenity? The columns are `osm_id`, `amenity_class`, `arrondissement_number` (integer), and `arrondissement_name` (string).
0:00
System info
{
"adapter": "openrouter",
"model": "deepseek/deepseek-v4-flash",
"base_url": "https://openrouter.ai/api/v1"
}
0:03
Let me start by reading the input files to understand their structure.
0:03
Bash
ls /work/
paris_amenities.gpkg
0:08
Let me first inspect the input files to understand their structure.
0:08
Bash
cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
amenities = gpd.read_file('paris_amenities.gpkg')
print('=== amenities ===')
print('columns:', list(amenities.columns))
print('crs:', amenities.crs)
print('shape:', amenities.shape)
print(amenities.head(3).to_string())
print()
# Check if arrondissements is also in the same file or separate
layers = gpd.list_layers('paris_amenities.gpkg')
print('layers:', layers)
"
=== amenities ===
columns: ['osm_id', 'amenity_class', 'name', 'geometry']
crs: EPSG:2154
shape: (85, 4)
osm_id amenity_class name geometry
0 9000000000 restaurant Le Grand Amour Restaurant POINT (652773.528 6864033.347)
1 9000000001 restaurant Talego POINT (652322.91 6861774.142)
2 9000000002 bakery Mamiche POINT (653028.103 6863582.051)
layers: name geometry_type
0 amenities Point
1 arrondissements Polygon
/usr/local/lib/python3.14/site-packages/pyogrio/geopandas.py:382: UserWarning: More than one layer found in 'paris_amenities.gpkg': 'amenities' (default), 'arrondissements'. Specify layer parameter to avoid this warning. result = read_func(
0:14
The GPKG has two layers: `amenities` (points) and `arrondissements` (polygons). I need to read both, perform a spatial join, and output the CSV with columns: `osm_id`, `amenity_class`, `arrondissement_number` (integer), `arrondissement_name` (string). Let me first inspect the arrondissements layer to understand its columns.
0:14
Bash
cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
arr = gpd.read_file('paris_amenities.gpkg', layer='arrondissements')
print('=== arrondissements ===')
print('columns:', list(arr.columns))
print('crs:', arr.crs)
print('shape:', arr.shape)
print(arr.head(5).to_string())
"
=== arrondissements ===
columns: ['id', 'name', 'geometry']
crs: EPSG:2154
shape: (20, 3)
id name geometry
0 0cef9694-93f0-4acf-a44f-f54a01fce855 Paris 13e Arrondissement POLYGON ((651737.858 6858104.126, 651824.872 6858010.988, 651879.152 6857920.158, 651878.75 6857915.913, 651876.549 6857905.524, 651874.039 6857895.96, 651873.83 6857886.732, 651869.177 6857863.153, 651840.43 6857717.337, 651837.951 6857698.276, 651836.206 6857679.043, 651836.072 6857676.253, 651827.749 6857499.967, 651865.954 6857478.445, 651861.715 6857537.514, 652007.983 6857514.829, 652022.343 6857512.587, 652044.198 6857509.204, 652064.249 6857523.804, 652078.81 6857534.392, 652108.197 6857555.621, 652122.233 6857565.813, 652137.895 6857577.181, 652150.631 6857586.427, 652160.464 6857593.574, 652164.401 6857596.41, 652174.877 6857604.007, 652448.903 6857802.594, 652704.918 6857515.663, 652755.98 6857516.17, 653011.548 6857518.574, 653255.012 6857520.876, 653317.012 6857550.132, 653352.58 6857567.059, 653458.445 6857614.255, 653518.475 6857646.231, 654047.126 6857898.644, 654080.73 6857914.756, 654185.04 6857964.792, 654314.057 6858030.591, 654316.608 6858031.894, 654320.242 6858033.744, 654385.141 6858065.146, 654408.676 6858076.536, 654410.858 6858077.587, 654414.189 6858079.195, 654532.979 6858136.562, 654590.02 6858216.753, 654770.688 6858311.892, 654858.156 6858357.945, 654998.184 6858432.302, 655007.112 6858437.048, 655009.206 6858438.155, 655124.743 6858499.117, 655128.135 6858500.903, 655130.033 6858502.412, 655199.438 6858557.551, 655234.729 6858580.162, 655043.631 6858784.339, 654979.865 6858862.37, 654295.066 6859707.248, 654111.087 6859965.421, 653972.59 6860160.28, 653942.12 6860191.39, 653937.655 6860196.596, 653688.174 6860479.88, 653473.234 6860729.416, 653408.541 6860674.915, 653399.768 6860665.478, 653393.077 6860655.725, 653389.382 6860648.059, 653386.152 6860637.889, 653384.725 6860632.096, 653381.16 6860622.217, 653339.29 6860538.488, 653267.204 6860394.179, 653250.264 6860360.423, 653213.476 6860286.674, 653185.345 6860230.602, 653158.334 6860179.803, 652425.223 6859832.457, 652420.2 6859831.376, 652412.091 6859831.609, 652278.043 6859856.018, 652215.385 6859867.532, 652084.264 6859891.51, 652070.241 6859894.684, 652020.712 6859911.083, 651957.626 6859931.988, 651948.695 6859934.92, 651709.008 6860013.683, 651708.543 6860008.082, 651707.418 6859995.493, 651706.834 6859988.759, 651702.013 6859931.711, 651696.369 6859870.166, 651694.565 6859845.773, 651694.17 6859840.595, 651677.685 6859688.526, 651676.85 6859682.517, 651676.272 6859676.562, 651671.272 6859630.646, 651670.689 6859625.024, 651670.097 6859619.169, 651668.309 6859606.408, 651667.79 6859602.276, 651653.068 6859491.735, 651646.962 6859444.439, 651644.911 6859430.034, 651643.806 6859421.659, 651642.132 6859410.097, 651635.353 6859361.361, 651634.786 6859314.574, 651635.245 6859283.291, 651640.611 6859239.257, 651642.693 6859116.556, 651650.138 6859017.285, 651658.095 6858959.085, 651659.049 6858952.861, 651664.504 6858899.987, 651666.097 6858871.852, 651667.291 6858839.773, 651666.85 6858808.886, 651666.008 6858792.448, 651665.266 6858753.691, 651667.354 6858700.299, 651667.665 6858691.835, 651669.696 6858642.224, 651661.737 6858561.162, 651661.87 6858548.007, 651661.904 6858544.126, 651657.629 6858486.751, 651657.151 6858478.727, 651656.647 6858471.147, 651648.708 6858380.144, 651669.105 6858271.837, 651681.214 6858235.041, 651691.566 6858204.954, 651730.162 6858120.792, 651737.858 6858104.126))
1 0e2667a3-715f-45ef-8fd5-7cdba7344a12 Paris 6e Arrondissement POLYGON ((651390.128 6862244.403, 651327.017 6862265.104, 651072.777 6862346.698, 651056.173 6862352.843,
[... truncated ...]4394.548 6861363.969, 654412.798 6861356.453, 654424.325 6861353.393, 654444.421 6861349.099, 654458.149 6861346.077, 654466.259 6861344.323, 654468.653 6861343.648, 654506.917 6861335.364, 654511.727 6861334.87, 654594.273 6861330.464, 654605.456 6861327.63, 654614.327 6861325.615, 654646.655 6861323.06, 654680.241 6861318.038, 654691.303 6861316.539, 654709.872 6861314.025, 654728.26 6861311.902, 654809.188 6861299.528, 654818.917 6861297.417, 654828.141 6861295.466, 654846.447 6861291.254, 654861.313 6861288.169, 654873.118 6861284.997, 654965.887 6861261.735, 655033.125 6861245.945, 655041.438 6861243.879, 655109.839 6861227.57, 655126.488 6861223.471, 655168.246 6861214.13, 655192.446 6861208.049, 655198.217 6861206.57, 655229.027 6861199.36, 655242.229 6861196.378, 655249.32 6861194.744, 655255.179 6861193.198, 655316.19 6861178.594, 655351.973 6861170.023, 655363.759 6861167.219, 655383.186 6861162.599, 655401.888 6861158.229, 655416.269 6861155.016, 655456.412 6861145.567, 655545.977 6861124.063, 655553.876 6861122.435, 655564.154 6861120.065, 655572.958 6861117.84, 655603.369 6861111.091, 655669.167 6861096.521, 655894.083 6861064.437, 655900.634 6861063.197, 655904.27 6861062.669, 655915.942 6861147.012, 655893.476 6861249.807, 655856.754 6861424.167, 655852.156 6861433.242, 655765.45 6861603.903, 655613.176 6861904.479, 655570.36 6862005.853, 655410.158 6862132.705, 655256.123 6862203.959, 655229.481 6862216.285, 655223.527 6862219.545, 655217.071 6862224.398, 655213.527 6862228.251, 655210.102 6862233.237, 655170.191 6862361.758, 655168.588 6862366.952, 655163.07 6862384.853, 655161.223 6862390.828, 655158.797 6862398.697, 655128.593 6862496.663, 655124.158 6862511.432, 655068.867 6862689.245, 655065.996 6862698.496, 655065.725 6862699.388, 655059.655 6862716.137, 655049.947 6862735.739, 654968.439 6862845.536, 654884.304 6862958.725, 654875.382 6862970.793, 654788.349 6863088.075, 654771.012 6863111.462, 654748.517 6863182.583, 654743.959 6863193.516, 654523.641 6863449.577, 654518.785 6863455.22, 654430.517 6863561.92, 654372.992 6863631.873, 654300.048 6863741.724, 654287.779 6863734.627, 654280.635 6863730.124, 654229.728 6863702.437, 654219.801 6863697.511, 654206.461 6863690.478, 654170.102 6863670.427, 654160.43 6863665.355, 654132.776 6863651.607, 654128.776 6863649.492, 654120.785 6863645.397, 654102.378 6863635.846, 654090.071 6863627.782, 654076.905 6863618.756, 654050.199 6863601.499, 654044.812 6863598.472, 654032.298 6863591.966, 654007.51 6863579.864, 653998.989 6863575.651, 653992.729 6863572.543, 653934.341 6863546.296, 653910.314 6863535.801, 653899.755 6863530.781, 653870.967 6863517.544))
3 32fbdc6a-f89d-4d02-ac87-6d0e4fc98969 Paris 3e Arrondissement POLYGON ((653556.757 6862647.528, 653554.105 6862669.077, 653552.52 6862678.13, 653552.177 6862678.433, 653552.416 6862678.954, 653544.933 6862727.519, 653541.67 6862749.652, 653536.529 6862763.682, 653535.436 6862766.337, 653532.984 6862772.662, 653523.305 6862797.982, 653515.315 6862818.996, 653512.516 6862825.79, 653508.303 6862836.51, 653490.77 6862881.498, 653484.72 6862896.48, 653482.518 6862901.814, 653481.654 6862903.789, 653473.973 6862924.923, 653468.664 6862937.998, 653463.768 6862951.392, 653463.251 6862952.82, 653448.422 6862989.968, 653443.704 6863002.616, 653437.662 6863016.754, 653420.869 6863057.766, 653415.956 6863070.771, 653410.206 6863086.53, 653402.19 6863107.845, 653401.254 6863110.91, 653400.425 6863113.619, 653400.351 6863114.531, 653400.126 6863117.513, 653403.066 6863131.912, 653362.51 6863212.769, 653331.205 6863240.833, 653290.958 6863278.82, 653135.931 6863313.132, 653132.987 6863313.734, 653084.663 6863324.334, 653078.876 6863325.448, 653034.228 6863335.14, 652997.369 6863344.802, 652968.254 6863351.287, 652943.13 6863357.73, 652904.471 6863366.039, 652785.685 6863393.583, 652764.286 6863400.819, 652756.729 6863403.416, 652748.368 6863406.342, 652745.494 6863407.399, 652740.761 6863409.028, 652728.559 6863413.186, 652716.266 6863418.013, 652631.949 6863447.714, 652572.06 6863291.923, 652532.891 6863187.872, 652425.991 6862905.034, 652383.376 6862792.851, 652362.903 6862740.688, 652322.54 6862635.904, 652328.468 6862634.131, 652335.937 6862631.535, 652370.492 6862619.641, 652377.859 6862617.101, 652381.378 6862615.849, 652432.776 6862597.49, 652490.459 6862577.846, 652493.298 6862576.866, 652505.033 6862572.811, 652556.695 6862554.285, 652567.657 6862549.058, 652570.921 6862547.085, 652575.579 6862544.289, 652606.25 6862528.437, 652624.705 6862518.89, 652639.23 6862511.376, 652646.221 6862507.727, 652681.923 6862488.81, 652689.524 6862484.344, 652697.865 6862480.551, 652764.004 6862446.685, 652772.953 6862441.919, 652794.637 6862430.589, 652805.294 6862425.654, 652816.099 6862418.138, 652821.153 6862414.349, 652917.515 6862303.723, 652946.526 6862269.26, 652952.389 6862263.008, 652990.498 6862228.505, 653074.111 6862165.633, 653097.01 6862150.036, 653100.929 6862147.491, 653161.75 6862107.624, 653163.976 6862106.171, 653171.132 6862101.865, 653175.463 6862099.362, 653197.993 6862087.971, 653242.3 6862065.596, 653249.673 6862061.845, 653255.777 6862059.015, 653350.244 6862015.576, 653355.792 6862012.974, 653364.416 6862008.779, 653369.913 6862006.11, 653393.816 6862000.258, 653405.448 6861995.071, 653458.253 6861981.681, 653463.137 6861980.497, 653468.483 6861979.108, 653522.385 6861965.376, 653534.259 6861964.603, 653572.929 6861954.685, 653577.308 6861953.46, 653581.686 6861952.257, 653650.822 6861934.902, 653664.983 6861933.832, 653664.169 6861939.432, 653661.809 6861952.539, 653660.201 6861961.626, 653657.965 6861976.578, 653653.048 6862009.476, 653650.485 6862026.643, 653645.86 6862057.56, 653645.056 6862063.471, 653643.736 6862071.744, 653641.641 6862086.005, 653640.187 6862095.869, 653637.663 6862112.48, 653634.15 6862135.604, 653632.945 6862143.676, 653631.725 6862150.735, 653629.508 6862163.441, 653628.082 6862172.204, 653619.361 6862233.122, 653617.888 6862243.475, 653616.717 6862250.189, 653614.1 6862268.803, 653613.468 6862273.345, 653606.659 6862320.915, 653603.934 6862336.204, 653602.288 6862346.926, 653597.527 6862378.144, 653595.694 6862390.168, 653595.359 6862392.339, 653593.22 6862408.336, 653592.191 6862415.394, 653584.603 6862466.573, 653583.062 6862476.56, 653580.304 6862495.864, 653577.975 6862511.128, 653576.003 6862524.12, 653571.277 6862555.072, 653566.711 6862585.032, 653556.757 6862647.528))
4 366fc115-880d-47a0-90d8-95f28f275224 Paris 2e Arrondissement POLYGON ((651998.253 6863647.264, 651855.796 6863684.309, 651823.845 6863692.625, 651812.756 6863695.509, 651799.005 6863698.548, 651705.999 6863723.353, 651592.07 6863754.795, 651527.213 6863736.689, 651524.89 6863736.097, 651523.5 6863735.742, 651460.488 6863719.867, 651446.427 6863716.594, 651444.068 6863715.991, 651422.387 6863710.257, 651390.418 6863702.274, 651375.782 6863698.56, 651369.555 6863696.933, 651359.11 6863694.375, 651306.993 6863681.546, 651288.395 6863676.965, 651217.037 6863658.962, 651204.907 6863655.862, 651192.88 6863652.749, 651179.088 6863649.174, 651159.158 6863644.004, 651146.984 6863640.849, 651085.418 6863624.61, 651040.372 6863614.416, 651028.776 6863612.902, 651015.073 6863609.415, 651004.951 6863606.987, 650856.361 6863569.092, 650837.248 6863563.45, 650814.779 6863558.314, 650783.253 6863550.042, 650781.518 6863549.634, 650723.114 6863535.352, 650712.204 6863533.432, 650705.339 6863531.822, 650716.17 6863520.121, 650717.798 6863518.328, 650723.63 6863512.396, 650762.209 6863469.178, 650809.135 6863417.26, 650864.504 6863358.121, 650871.087 6863351.471, 650880.608 6863347.031, 650901.562 6863337.813, 650977.559 6863310.459, 651013.719 6863297.52, 651019.286 6863295.65, 651025.238 6863293.409, 651104.047 6863265.299, 651119.098 6863259.812, 651133.075 6863254.757, 651136.563 6863253.404, 651187.289 6863234.773, 651193.915 6863232.359, 651234.966 6863217.269, 651241.329 6863214.969, 651275.666 6863202.326, 651281.056 6863200.345, 651286.607 6863198.33, 651331.178 6863182.121, 651381.585 6863163.794, 651384.284 6863162.815, 651389.754 6863160.757, 651397.134 6863158.137, 651480.294 6863127.916, 651485.209 6863126.129, 651490.826 6863124.059, 651514.69 6863115.219, 651528.932 6863110.229, 651542.39 6863105.335, 651551.752 6863101.931, 651557.325 6863099.905, 651575.076 6863093.408, 651581.812 6863090.972, 651619.188 6863077.404, 651633.757 6863072.112, 651635.132 6863071.611, 651646.023 6863067.661, 651668.887 6863059.342, 651794.491 6863012.403, 651797.007 6863011.459, 651816.93 6863004.088, 651818.809 6863003.305, 651821.178 6863002.418, 651863.51 6862986.598, 651911.525 6862968.652, 651933.005 6862960.623, 651993.052 6862938.185, 652070.827 6862909.119, 652076.693 6862906.957, 652079.728 6862905.809, 652138.877 6862883.803, 652143.215 6862882.21, 652202.598 6862860.103, 652213.912 6862855.884, 652231.481 6862849.356, 652243.345 6862844.944, 652251.259 6862841.998, 652261.857 6862838.03, 652268.074 6862835.744, 652306.357 6862821.506, 652309.538 6862820.324, 652318.279 6862817.06, 652320.948 6862816.071, 652353.76 6862803.869, 652369.149 6862798.138, 652372.36 6862796.955, 652377.488 6862795.045, 652381.949 6862793.385, 652383.376 6862792.851, 652425.991 6862905.034, 652532.891 6863187.872, 652572.06 6863291.923, 652631.949 6863447.714, 652596.036 6863460.673, 652539.762 6863480.227, 652527.588 6863484.297, 652511.036 6863489.348, 652506.266 6863490.955, 652498.578 6863493.553, 652495.981 6863494.43, 652493.376 6863495.297, 652486.997 6863497.462, 652457.283 6863507.581, 652422.272 6863519.511, 652389.946 6863531.519, 652373.566 6863536.869, 652357.517 6863542.472, 652323.945 6863553.601, 652301.969 6863560.932, 652288.346 6863565.348, 652253.892 6863576.14, 652235.183 6863582.01, 652225.239 6863585.117, 652194.282 6863594.813, 652177.984 6863600.319, 652167.2 6863602.943, 652152.175 6863607.226, 652087.065 6863624.155, 652081.033 6863625.729, 652034.479 6863637.835, 652025.893 6863640.063, 652006.59 6863645.094, 651998.253 6863647.264))
0:21
I have: - `amenities` with columns: `osm_id`, `amenity_class`, `name`, `geometry` (Point, EPSG:2154) - `arrondissements` with columns: `id`, `name`, `geometry` (Polygon, EPSG:2154) The names are like "Paris 13e Arrondissement" - I need to extract the arrondissement number from that. The numbers are: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20. I need to do a spatial join: for each amenity point, find which arrondissement polygon it falls inside. Let me write the script.
0:21
Bash
cd /work && python3 -c "
cd /work && python3 -c "
import geopandas as gpd
arr = gpd.read_file('paris_amenities.gpkg', layer='arrondissements')
print('Arrondissement names:')
for n in arr['name']:
print(repr(n))
"
Arrondissement names: 'Paris 13e Arrondissement' 'Paris 6e Arrondissement' 'Paris 11e Arrondissement' 'Paris 3e Arrondissement' 'Paris 2e Arrondissement' 'Paris 10e Arrondissement' 'Paris 20e Arrondissement' 'Paris 8e Arrondissement' 'Paris 19e Arrondissement' 'Paris 5e Arrondissement' 'Paris 17e Arrondissement' 'Paris 9e Arrondissement' 'Paris 16e Arrondissement' 'Paris 14e Arrondissement' 'Paris 12e Arrondissement' 'Paris 4e Arrondissement' 'Paris 18e Arrondissement' 'Paris 7e Arrondissement' 'Paris 1er Arrondissement' 'Paris 15e Arrondissement'
0:34
Now I have a clear picture. I need to: 1. Read the amenities (points) and arrondissements (polygons) from the GPKG 2. Perform a spatial join — for each point, find the arrondissement polygon that contains it 3. Extract the arrondissement number from the name string (e.g., "Paris 13e Arrondissement" -> 13, "Paris 1er Arrondissement" -> 1) 4. Write to CSV with columns: osm_id, amenity_class, arrondissement_number (int), arrondissement_name (string) Let me parse the arrondissement number. The names are like: - "Paris 13e Arrondissement" - "Paris 1er Arrondissement" - "Paris 2e Arrondissement" - etc. So I need to extract the number from the name. The pattern is "Paris (\d+)" basically, but "1er" is special. Let me use a regex to extract the digits. Let me write the script.
0:34
Write
/work/solve.py
content · 37 lines · py
import re
import geopandas as gpd
# Read data
amenities = gpd.read_file("/work/paris_amenities.gpkg", layer="amenities")
arrondissements = gpd.read_file("/work/paris_amenities.gpkg", layer="arrondissements")
# Both are in EPSG:2154 — perform spatial join
joined = gpd.sjoin(
amenities,
arrondissements,
how="left",
predicate="within",
)
# Extract arrondissement number from the name string
def extract_number(name):
if pd.isna(name):
return None
m = re.search(r"(\d+)", name)
if m:
return int(m.group(1))
return None
import pandas as pd
joined["arrondissement_number"] = joined["name_right"].apply(extract_number)
joined["arrondissement_name"] = joined["name_right"]
# Build output
result = joined[["osm_id", "amenity_class", "arrondissement_number", "arrondissement_name"]].copy()
result["arrondissement_number"] = result["arrondissement_number"].astype("Int64") # nullable int
result.to_csv("/work/amenity_to_arrondissement.csv", index=False)
print(f"Wrote {len(result)} rows to amenity_to_arrondissement.csv")
print(result.head(10).to_string())Wrote /work/solve.py (1104 chars).
0:40
Wait, the Write succeeded but the tool output says "Wrote" — it looks like it ran the script too? No, the Write tool just writes content and returns "Wrote /work/solve.py (1104 chars)." That's just the write confirmation. I need to run the script. Actually looking at the output more carefully - the Write tool returned "Wrote /work/solve.py (1104 chars)." with no execution - that's just the file write. Let me run it.
0:40
Bash
cd /work && python3 solve.py
Wrote 85 rows to amenity_to_arrondissement.csv
osm_id amenity_class arrondissement_number arrondissement_name
0 9000000000 restaurant 10 Paris 10e Arrondissement
1 9000000001 restaurant 4 Paris 4e Arrondissement
2 9000000002 bakery 10 Paris 10e Arrondissement
3 9000000003 bakery 13 Paris 13e Arrondissement
4 9000000004 restaurant 9 Paris 9e Arrondissement
5 9000000005 restaurant 15 Paris 15e Arrondissement
6 9000000006 restaurant 20 Paris 20e Arrondissement
7 9000000007 cafe 6 Paris 6e Arrondissement
8 9000000008 restaurant 18 Paris 18e Arrondissement
9 9000000009 cafe 5 Paris 5e Arrondissement
0:54
The output looks correct. Let me verify the CSV file exists and check its contents.
0:54
Bash
cd /work && ls -la amenity_to_arrondissement.csv && echo "---" && head -5 amenit...
-rw-r--r-- 1 agent agent 3988 Jun 9 07:33 amenity_to_arrondissement.csv --- osm_id,amenity_class,arrondissement_number,arrondissement_name 9000000000,restaurant,10,Paris 10e Arrondissement 9000000001,restaurant,4,Paris 4e Arrondissement 9000000002,bakery,10,Paris 10e Arrondissement 9000000003,bakery,13,Paris 13e Arrondissement
1:19
Let me verify a few things: 1. All 85 amenities have a match? Let me check if any have null arrondissement. 2. The column names are correct: `osm_id`, `amenity_class`, `arrondissement_number` (integer), `arrondissement_name` (string). 3. The arrondissement_number is integer (note: "1er" is a special case — let me check that it got the number 1 correctly). Let me verify.
1:19
Bash
cd /work && python3 -c "
cd /work && python3 -c "
import pandas as pd
df = pd.read_csv('amenity_to_arrondissement.csv')
print('Shape:', df.shape)
print('Null arrondissement_number:', df['arrondissement_number'].isna().sum())
print('Null arrondissement_name:', df['arrondissement_name'].isna().sum())
print()
print('dtypes:', df.dtypes)
print()
# Check 1er Arrondissement
print('Rows for 1er Arrondissement:')
print(df[df['arrondissement_name'].str.contains('1er', na=False)].to_string())
"
Shape: (85, 4)
Null arrondissement_number: 0
Null arrondissement_name: 0
dtypes: osm_id int64
amenity_class str
arrondissement_number int64
arrondissement_name str
dtype: object
Rows for 1er Arrondissement:
osm_id amenity_class arrondissement_number arrondissement_name
13 9000000013 restaurant 1 Paris 1er Arrondissement
35 9000000035 cafe 1 Paris 1er Arrondissement
47 9000000047 cafe 1 Paris 1er Arrondissement
53 9000000053 cafe 1 Paris 1er Arrondissement
83 9000000083 library 1 Paris 1er Arrondissement
1:29
Everything looks good. Let me verify the output criteria: 1. File: `amenity_to_arrondissement.csv` ✓ 2. One row per amenity (85 amenities -> 85 rows) ✓ 3. Columns: `osm_id`, `amenity_class`, `arrondissement_number` (integer), `arrondissement_name` (string) ✓ 4. No nulls ✓ 5. `arrondissement_number` is integer type (Int64) ✓ 6. The 1er Arrondissement has number 1 (not an issue - "1er" is in the name which is correct) ✓ All good!
1:29