The MET API

The MET API#

This session examines how to use the MET API in practice to gather and explore data.

Through the session, we will:

learn the components of an API request: the root, path, and endpoint
practice with a few handy functions for examining request data
- type() and dir()
learn about a super important data type, the dictionary or dict, and how to access items within that structure.
create more requests with that data
- f-strings
sort through request data using loops and conditionals
transform our data into a dataframe, for doing simple data analysis

import requests

# the structure of our request: base_url, path, query

base_url = "https://collectionapi.metmuseum.org"
path = "/public/collection/v1/search"
query = "?q=woman"

the anatomy of an API request:#

the root which consists of the base URL.
- https://collectionapi.metmuseum.org/
the path which consists of a directory structure (file structure) where the data is held.
- /public/collection/v1/objects
- /public/collection/v1/departments
- /public/collection/v1/search
the parameter or the endpoint which is the specific request. For example, a query parameter takes a search term following ?q=, like:
- ?q=woman
- ?q=van+gogh

A complete sample request that searches for the “woman” keyword would be:

https://collectionapi.metmuseum.org/public/collection/v1/search?q=woman

To read more about the MET API, see here: https://metmuseum.github.io/

# the request, saved to a variable

url = f'{base_url}{path}{query}'
women = requests.get(url)

inspecting objects: two functions: `type()` and `dir()`#

Using type() and dir() to better understand our response data. The end goal is to sift through the data to discover interesting things.

# what type of object do we have?

type(women)

requests.models.Response

What can we do with a Response object? Spend a couple of minutes exploring the different methods.

dir(women)

['__attrs__',
 '__bool__',
 '__class__',
 '__delattr__',
 '__dict__',
 '__dir__',
 '__doc__',
 '__enter__',
 '__eq__',
 '__exit__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__getstate__',
 '__gt__',
 '__hash__',
 '__init__',
 '__init_subclass__',
 '__iter__',
 '__le__',
 '__lt__',
 '__module__',
 '__ne__',
 '__new__',
 '__nonzero__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__setattr__',
 '__setstate__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 '__weakref__',
 '_content',
 '_content_consumed',
 '_next',
 'apparent_encoding',
 'close',
 'connection',
 'content',
 'cookies',
 'elapsed',
 'encoding',
 'headers',
 'history',
 'is_permanent_redirect',
 'is_redirect',
 'iter_content',
 'iter_lines',
 'json',
 'links',
 'next',
 'ok',
 'raise_for_status',
 'raw',
 'reason',
 'request',
 'status_code',
 'text',
 'url']

women.headers

{'Content-Type': 'application/json', 'Vary': 'Origin', 'X-Powered-By': 'ARR/3.0, ASP.NET', 'Date': 'Wed, 05 Nov 2025 14:43:59 GMT', 'Set-Cookie': 'visid_incap_1662004=AzsDAwU8S8mFdht29aHeUq5iC2kAAAAAQUIPAAAAAADYUY2DR4fdvhhQ2JWc5xQa; expires=Thu, 05 Nov 2026 06:37:48 GMT; HttpOnly; path=/; Domain=.metmuseum.org, incap_ses_703_1662004=BjucGHeruh9qcgSbOI/BCa9iC2kAAAAAqxcDiE2Rl2dpGKJh0bC/7A==; path=/; Domain=.metmuseum.org', 'X-CDN': 'Imperva', 'Content-Encoding': 'gzip', 'Transfer-Encoding': 'chunked', 'X-Iinfo': '10-13151182-13151183 NNYN CT(98 189 0) RT(1762353839351 159) q(0 0 3 0) r(9 9) U12'}

women.raw

<urllib3.response.HTTPResponse at 0x1156e5c90>

women.elapsed

datetime.timedelta(seconds=1, microseconds=472696)

women.ok

True

women

<Response [200]>

.json() to parse our response object#

# why do we need to add parenthesis? 
parsed = women.json()

type(parsed)

dict

what is a dict? 2D data. We will look more closely soon.

dir(parsed)

['__class__',
 '__class_getitem__',
 '__contains__',
 '__delattr__',
 '__delitem__',
 '__dir__',
 '__doc__',
 '__eq__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__getitem__',
 '__getstate__',
 '__gt__',
 '__hash__',
 '__init__',
 '__init_subclass__',
 '__ior__',
 '__iter__',
 '__le__',
 '__len__',
 '__lt__',
 '__ne__',
 '__new__',
 '__or__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__reversed__',
 '__ror__',
 '__setattr__',
 '__setitem__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 'clear',
 'copy',
 'fromkeys',
 'get',
 'items',
 'keys',
 'pop',
 'popitem',
 'setdefault',
 'update',
 'values']

parsed.keys()

dict_keys(['total', 'objectIDs'])

We access items from a dict with brackets[].

accessing items from a `dict`#

What is a dictionary anyway?

instructor = {
    'name': ['filipa calado', 'patrick smyth', 'stephen zweibel'],
    'age': [35, 37, 38],
    'degree': ['literature', 'literature', 'library science'],
    'job': ['digital scholarship specialist', 'startup', 'digital scholarship librarian']
}

# see the keys

instructor.keys()

dict_keys(['name', 'age', 'degree', 'job'])

# access items through brackets containing keys

instructor['name']

['filipa calado', 'patrick smyth', 'stephen zweibel']

similar to a DataFrame in pandas#

import pandas as pd
df = pd.DataFrame(instructor)

A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.1 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Traceback (most recent call last):  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/runpy.py", line 198, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/runpy.py", line 88, in _run_code
    exec(code, run_globals)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel_launcher.py", line 18, in <module>
    app.launch_new_instance()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/traitlets/config/application.py", line 1075, in launch_instance
    app.start()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelapp.py", line 739, in start
    self.io_loop.start()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/tornado/platform/asyncio.py", line 205, in start
    self.asyncio_loop.run_forever()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/base_events.py", line 608, in run_forever
    self._run_once()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/base_events.py", line 1936, in _run_once
    handle._run()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/events.py", line 84, in _run
    self._context.run(self._callback, *self._args)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 545, in dispatch_queue
    await self.process_one()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 534, in process_one
    await dispatch(*args)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 437, in dispatch_shell
    await result
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/ipkernel.py", line 362, in execute_request
    await super().execute_request(stream, ident, parent)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 778, in execute_request
    reply_content = await reply_content
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/ipkernel.py", line 449, in do_execute
    res = shell.run_cell(
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/zmqshell.py", line 549, in run_cell
    return super().run_cell(*args, **kwargs)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3075, in run_cell
    result = self._run_cell(
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3130, in _run_cell
    result = runner(coro)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/async_helpers.py", line 128, in _pseudo_sync_runner
    coro.send(None)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3334, in run_cell_async
    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3517, in run_ast_nodes
    if await self.run_code(code, result, async_=asy):
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3577, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "/var/folders/z6/8hbw1n6n3dq2jdw3_zjysj5sws21gh/T/ipykernel_71578/3454732655.py", line 1, in <module>
    import pandas as pd
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/__init__.py", line 26, in <module>
    from pandas.compat import (
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/compat/__init__.py", line 27, in <module>
    from pandas.compat.pyarrow import (
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/compat/pyarrow.py", line 8, in <module>
    import pyarrow as pa
  File "/Users/fcalado/.local/lib/python3.11/site-packages/pyarrow/__init__.py", line 65, in <module>
    import pyarrow.lib as _lib

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
AttributeError: _ARRAY_API not found

A module that was compiled using NumPy 1.x cannot be run in
NumPy 2.0.1 as it may crash. To support both 1.x and 2.x
versions of NumPy, modules must be compiled with NumPy 2.0.
Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.

If you are a user of the module, the easiest solution will be to
downgrade to 'numpy<2' or try to upgrade the affected module.
We expect that some modules will need time to support NumPy 2.

Traceback (most recent call last):  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/runpy.py", line 198, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/runpy.py", line 88, in _run_code
    exec(code, run_globals)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel_launcher.py", line 18, in <module>
    app.launch_new_instance()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/traitlets/config/application.py", line 1075, in launch_instance
    app.start()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelapp.py", line 739, in start
    self.io_loop.start()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/tornado/platform/asyncio.py", line 205, in start
    self.asyncio_loop.run_forever()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/base_events.py", line 608, in run_forever
    self._run_once()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/base_events.py", line 1936, in _run_once
    handle._run()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/asyncio/events.py", line 84, in _run
    self._context.run(self._callback, *self._args)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 545, in dispatch_queue
    await self.process_one()
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 534, in process_one
    await dispatch(*args)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 437, in dispatch_shell
    await result
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/ipkernel.py", line 362, in execute_request
    await super().execute_request(stream, ident, parent)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/kernelbase.py", line 778, in execute_request
    reply_content = await reply_content
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/ipkernel.py", line 449, in do_execute
    res = shell.run_cell(
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/ipykernel/zmqshell.py", line 549, in run_cell
    return super().run_cell(*args, **kwargs)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3075, in run_cell
    result = self._run_cell(
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3130, in _run_cell
    result = runner(coro)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/async_helpers.py", line 128, in _pseudo_sync_runner
    coro.send(None)
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3334, in run_cell_async
    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3517, in run_ast_nodes
    if await self.run_code(code, result, async_=asy):
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/IPython/core/interactiveshell.py", line 3577, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "/var/folders/z6/8hbw1n6n3dq2jdw3_zjysj5sws21gh/T/ipykernel_71578/3454732655.py", line 1, in <module>
    import pandas as pd
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/__init__.py", line 49, in <module>
    from pandas.core.api import (
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/core/api.py", line 9, in <module>
    from pandas.core.dtypes.dtypes import (
  File "/Users/fcalado/.conda/envs/jb/lib/python3.11/site-packages/pandas/core/dtypes/dtypes.py", line 24, in <module>
    from pandas._libs import (
  File "/Users/fcalado/.local/lib/python3.11/site-packages/pyarrow/__init__.py", line 65, in <module>
    import pyarrow.lib as _lib

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
AttributeError: _ARRAY_API not found

df

	name	age	degree	job
0	filipa calado	35	literature	digital scholarship specialist
1	patrick smyth	37	literature	startup
2	stephen zweibel	38	library science	digital scholarship librarian

# let's try with the first object

parsed.keys()

dict_keys(['total', 'objectIDs'])

We access items from a dict using brackets.

# just printing out the first ten
parsed['objectIDs'][:10]

type(parsed['objectIDs'])

list

parsed['objectIDs'][0]

individual challenge:#

Reading the docs for the “Search” endpoint, play around with the different parameters. Try do searches for isHighlight, or dateBegin and dateEnd. You can layer parameters by using the & character in between them.

using the “objects” endpoint#

So far, we have been using the “search” endpoint for our requests. Now, we will create a new request using the “objects” endpoint”. with data from the original request

Now we past the URL for “object” (rather than search), and we do it within an f-string, putting the variable “first” into curly brackets at the end.

first = parsed['objectIDs'][0]
path = '/public/collection/v1/objects/'

# the base_url stays the same, so we don't need to change it.

url = f"{base_url}{path}{first}"

# running the request

first_object = requests.get(url)

# checking the resulting object

first_object

<Response [200]>

dir(first_object)

['__attrs__',
 '__bool__',
 '__class__',
 '__delattr__',
 '__dict__',
 '__dir__',
 '__doc__',
 '__enter__',
 '__eq__',
 '__exit__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__getstate__',
 '__gt__',
 '__hash__',
 '__init__',
 '__init_subclass__',
 '__iter__',
 '__le__',
 '__lt__',
 '__module__',
 '__ne__',
 '__new__',
 '__nonzero__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__setattr__',
 '__setstate__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 '__weakref__',
 '_content',
 '_content_consumed',
 '_next',
 'apparent_encoding',
 'close',
 'connection',
 'content',
 'cookies',
 'elapsed',
 'encoding',
 'headers',
 'history',
 'is_permanent_redirect',
 'is_redirect',
 'iter_content',
 'iter_lines',
 'json',
 'links',
 'next',
 'ok',
 'raise_for_status',
 'raw',
 'reason',
 'request',
 'status_code',
 'text',
 'url']

look at the json for the first object

# all of the data about this object
# look at the URL! 

first_object.json()

{'objectID': 483873,
 'isHighlight': False,
 'accessionNumber': '1984.613.2',
 'accessionYear': '1984',
 'isPublicDomain': False,
 'primaryImage': '',
 'primaryImageSmall': '',
 'additionalImages': [],
 'constituents': [{'constituentID': 161817,
   'role': 'Artist',
   'name': 'Willem de Kooning',
   'constituentULAN_URL': 'http://vocab.getty.edu/page/ulan/500000974',
   'constituentWikidata_URL': 'https://www.wikidata.org/wiki/Q132305',
   'gender': ''}],
 'department': 'Modern and Contemporary Art',
 'objectName': 'Painting',
 'title': 'Woman',
 'culture': '',
 'period': '',
 'dynasty': '',
 'reign': '',
 'portfolio': '',
 'artistRole': 'Artist',
 'artistPrefix': '',
 'artistDisplayName': 'Willem de Kooning',
 'artistDisplayBio': 'American (born The Netherlands), Rotterdam 1904–1997 East Hampton, New York',
 'artistSuffix': '',
 'artistAlphaSort': 'De Kooning, Willem',
 'artistNationality': 'American, born The Netherlands',
 'artistBeginDate': '1904',
 'artistEndDate': '1997',
 'artistGender': '',
 'artistWikidata_URL': 'https://www.wikidata.org/wiki/Q132305',
 'artistULAN_URL': 'http://vocab.getty.edu/page/ulan/500000974',
 'objectDate': '1944',
 'objectBeginDate': 1944,
 'objectEndDate': 1944,
 'medium': 'Oil and charcoal on canvas',
 'dimensions': '45 7/8 × 31 3/4 in. (116.5 × 80.6 cm)',
 'measurements': [{'elementName': 'Overall',
   'elementDescription': None,
   'elementMeasurements': {'Height': 116.522736, 'Width': 80.645164}},
  {'elementName': 'Framed',
   'elementDescription': 'F.1.1984.613.2  Brown wood float w//AR plexi',
   'elementMeasurements': {'Depth': 9.207519,
    'Height': 125.730255,
    'Width': 90.48768}}],
 'creditLine': 'From the Collection of Thomas B. Hess, Gift of the heirs of Thomas B. Hess, 1984',
 'geographyType': '',
 'city': '',
 'state': '',
 'county': '',
 'country': '',
 'region': '',
 'subregion': '',
 'locale': '',
 'locus': '',
 'excavation': '',
 'river': '',
 'classification': 'Paintings',
 'rightsAndReproduction': '© 2025 Artists Rights Society (ARS), New York',
 'linkResource': '',
 'metadataDate': '2025-10-02T04:53:22.577Z',
 'repository': 'Metropolitan Museum of Art, New York, NY',
 'objectURL': 'https://www.metmuseum.org/art/collection/search/483873',
 'tags': [{'term': 'Women',
   'AAT_URL': 'http://vocab.getty.edu/page/aat/300025943',
   'Wikidata_URL': 'https://www.wikidata.org/wiki/Q467'}],
 'objectWikidata_URL': 'https://www.wikidata.org/wiki/Q20189686',
 'isTimelineWork': False,
 'GalleryNumber': ''}

# now we can save this first object to its own variable. 
# will make it easier to do more things to it!

first_json = first_object.json()

individual practice:#

Take a few minutes to inspect the dataset by using different keys.

Why do you think there’s no gender?

# no result!

first_json['artistGender']

''

first_json['department']

'Modern and Contemporary Art'

first_json['culture']

''

looping through our objects#

We are going to create a larger collection of object information (the metadata about each art object in the search results), so that we can loop through the objects to find out more about the artist’s gender.

making a list of ids#

# first, print out the first 10 items in the objectIDs list
parsed['objectIDs'][:10]

ids = parsed['objectIDs'][:10]

# remember we can slice our list, to get just the first ten

for item in ids:
    print(item)

type(ids)

list

len(ids)

Now let’s go back to the original list, and pull out all the info for the results.

making a new request#

Remember how to make a new request, using an f-string

url = f'{base_url}{path}{item}

Now, add that request to your loop so you make a new request for the first ten items on the list of object IDs. Once you get the response, parse it (with json()) and append that item to a new list.

first_ten = []
for item in ids:
    # passing the objectID variable into the URL
    base_url = 'https://collectionapi.metmuseum.org'
    path = '/public/collection/v1/objects/'
    url = f'{base_url}{path}{item}'
    # grabbing our response for that object
    response = requests.get(url)
    # parsing our response with json
    parsed = response.json()
    # appending the response to our new list
    first_ten.append(parsed)

# because we already know the first, let's check the last item

first_ten[-1]

{'message': 'Not a valid object'}

now guess what type of data we have for first_ten?

type(first_ten)

list

group challenge:#

Write a loop to print out information about some of the keys for each object. For example, print out the value of artistDisplayName.

for item in first_ten:
    print(item['artistDisplayName'])

Willem de Kooning
Royal Porcelain Manufactory, Naples

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Cell In[42], line 2
      1 for item in first_ten:
----> 2     print(item['artistDisplayName'])

KeyError: 'artistDisplayName'

let’s look at some of the values

for item in first_ten:
    print(item['title'])

Woman
Woman
Terracotta lekythos (oil flask)
Woman
Woman

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
Cell In[39], line 2
      1 for item in first_ten:
----> 2     print(item['title'])

KeyError: 'title'

There’s another way to grab items from a dict, using the get() method.

dir(item)

['__class__',
 '__class_getitem__',
 '__contains__',
 '__delattr__',
 '__delitem__',
 '__dir__',
 '__doc__',
 '__eq__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__getitem__',
 '__getstate__',
 '__gt__',
 '__hash__',
 '__init__',
 '__init_subclass__',
 '__ior__',
 '__iter__',
 '__le__',
 '__len__',
 '__lt__',
 '__ne__',
 '__new__',
 '__or__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__reversed__',
 '__ror__',
 '__setattr__',
 '__setitem__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 'clear',
 'copy',
 'fromkeys',
 'get',
 'items',
 'keys',
 'pop',
 'popitem',
 'setdefault',
 'update',
 'values']

for item in first_ten:
    if item.get('artistDisplayName'):
        print(item['artistDisplayName'])

Willem de Kooning
Royal Porcelain Manufactory, Naples
Woman Painter
Man Ray
Willem de Kooning
Joan Miró
Willem de Kooning
Harold Anchel
Alexander Calder

for item in first_ten:
    title = item.get('artistDisplayName')
    print(title)

Willem de Kooning
Royal Porcelain Manufactory, Naples
Woman Painter
Man Ray
Willem de Kooning
None
Joan Miró
Willem de Kooning
Harold Anchel
Alexander Calder

about “women”#

Let’s make our dataset bigger, with 50 works.

first_fifty = []
for item in parsed['objectIDs'][:50]:
    url = f'https://collectionapi.metmuseum.org/public/collection/v1/objects/{item}'
    response = requests.get(url)
    parsed = response.json()
    first_fifty.append(parsed)

# combine get() with conditional to get rid of the None's

for item in first_fifty:
    if item.get('artistDisplayName'):
        print(item['artistDisplayName'])

# or, if we want to show the value, even if empty or None

for item in first_hundred:
    gender = item.get('artistGender')
    print(gender)

None

None

None

None

Female

Female

Female

Let’s use get() combined with f-strings to print both the name and the gender.

# why do you think we see only female?

for item in first_fifty:
    if item.get('artistDisplayName'):
        print(f"artist name: {item['artistDisplayName']}")
        print(f"artist gender: {item['artistGender']}")

artist name: Willem de Kooning
artist gender: 
artist name: Royal Porcelain Manufactory, Naples
artist gender: 
artist name: Woman Painter
artist gender: 
artist name: Man Ray
artist gender: 
artist name: Willem de Kooning
artist gender: 
artist name: Joan Miró
artist gender: 
artist name: Willem de Kooning
artist gender: 
artist name: Alexander Calder
artist gender: 
artist name: Harold Anchel
artist gender: 
artist name: Malick Sidibé
artist gender: 
artist name: Joan Miró
artist gender: 
artist name: Joan Miró
artist gender: 
artist name: Lorenzo Mosca
artist gender: 
artist name: Bow Porcelain Factory
artist gender: 
artist name: Royal Porcelain Manufactory, Berlin
artist gender: 
artist name: Vienna
artist gender: 
artist name: Edgar Degas
artist gender: 
artist name: Gaston Lachaise
artist gender: 
artist name: Fernand Léger
artist gender: 
artist name: Edgar Degas
artist gender: 
artist name: Frans Hals
artist gender: 
artist name: Jean Dubuffet
artist gender: 
artist name: Edgar Degas
artist gender: 
artist name: Fra Filippo Lippi
artist gender: 
artist name: Rembrandt (Rembrandt van Rijn)
artist gender: 
artist name: Gustave Courbet
artist gender: 
artist name: Quinten Massys
artist gender: 
artist name: Jean-François Millet
artist gender: 
artist name: Henri Fantin-Latour
artist gender: 
artist name: Charles-Henri-Joseph Cordier
artist gender: 
artist name: Louis Anquetin
artist gender: 
artist name: Pablo Picasso
artist gender: 
artist name: Bastis Master
artist gender: 
artist name: Ruth Ava Lyons
artist gender: Female
artist name: Christian Julia
artist gender: 
artist name: Johannes Vermeer
artist gender: 
artist name: Georges Braque
artist gender: 
artist name: Gustave Courbet
artist gender: 
artist name: Johannes Vermeer
artist gender: 
artist name: Orazio Borgianni
artist gender: 
artist name: Antoine Watteau
artist gender: 
artist name: Johannes Vermeer
artist gender: 
artist name: Berthe Morisot
artist gender: Female
artist name: Charles-Henri-Joseph Cordier
artist gender: 
artist name: Gustave Courbet
artist gender: 
artist name: Louise Bourgeois
artist gender: Female
artist name: Edgar Degas
artist gender: 
artist name: Rembrandt (Rembrandt van Rijn)
artist gender: 
artist name: Petrus Christus
artist gender: 
artist name: Léon Bonnat
artist gender: 
artist name: Pablo Picasso
artist gender: 
artist name: Master of Rimini
artist gender: 

saving to DataFrame#

# look again at the first object
first_fifty[0]

{'objectID': 483873,
 'isHighlight': False,
 'accessionNumber': '1984.613.2',
 'accessionYear': '1984',
 'isPublicDomain': False,
 'primaryImage': '',
 'primaryImageSmall': '',
 'additionalImages': [],
 'constituents': [{'constituentID': 161817,
   'role': 'Artist',
   'name': 'Willem de Kooning',
   'constituentULAN_URL': 'http://vocab.getty.edu/page/ulan/500000974',
   'constituentWikidata_URL': 'https://www.wikidata.org/wiki/Q132305',
   'gender': ''}],
 'department': 'Modern and Contemporary Art',
 'objectName': 'Painting',
 'title': 'Woman',
 'culture': '',
 'period': '',
 'dynasty': '',
 'reign': '',
 'portfolio': '',
 'artistRole': 'Artist',
 'artistPrefix': '',
 'artistDisplayName': 'Willem de Kooning',
 'artistDisplayBio': 'American (born The Netherlands), Rotterdam 1904–1997 East Hampton, New York',
 'artistSuffix': '',
 'artistAlphaSort': 'De Kooning, Willem',
 'artistNationality': 'American, born The Netherlands',
 'artistBeginDate': '1904',
 'artistEndDate': '1997',
 'artistGender': '',
 'artistWikidata_URL': 'https://www.wikidata.org/wiki/Q132305',
 'artistULAN_URL': 'http://vocab.getty.edu/page/ulan/500000974',
 'objectDate': '1944',
 'objectBeginDate': 1944,
 'objectEndDate': 1944,
 'medium': 'Oil and charcoal on canvas',
 'dimensions': '45 7/8 × 31 3/4 in. (116.5 × 80.6 cm)',
 'measurements': [{'elementName': 'Overall',
   'elementDescription': None,
   'elementMeasurements': {'Height': 116.522736, 'Width': 80.645164}},
  {'elementName': 'Frame',
   'elementDescription': 'F.1.1984.613.2 Brown wood float frame-AR Pexi',
   'elementMeasurements': {'Depth': 9.207519,
    'Height': 125.730255,
    'Width': 90.80518}}],
 'creditLine': 'From the Collection of Thomas B. Hess, Gift of the heirs of Thomas B. Hess, 1984',
 'geographyType': '',
 'city': '',
 'state': '',
 'county': '',
 'country': '',
 'region': '',
 'subregion': '',
 'locale': '',
 'locus': '',
 'excavation': '',
 'river': '',
 'classification': 'Paintings',
 'rightsAndReproduction': '© 2024 Artists Rights Society (ARS), New York',
 'linkResource': '',
 'metadataDate': '2024-09-21T04:53:05.127Z',
 'repository': 'Metropolitan Museum of Art, New York, NY',
 'objectURL': 'https://www.metmuseum.org/art/collection/search/483873',
 'tags': [{'term': 'Women',
   'AAT_URL': 'http://vocab.getty.edu/page/aat/300025943',
   'Wikidata_URL': 'https://www.wikidata.org/wiki/Q467'}],
 'objectWikidata_URL': 'https://www.wikidata.org/wiki/Q20189686',
 'isTimelineWork': False,
 'GalleryNumber': ''}

# let's get a bunch of this data into lists

titles = []
names = []
genders = []
depts = []
countries = []
urls = []

for item in first_fifty:
    title = item.get('artistGender')
    titles.append(title)
    name = item.get('artistDisplayName')
    names.append(name)
    gender = item.get('artistGender')
    genders.append(gender)
    dept = item.get('department')
    depts.append(dept)
    country = item.get('country')
    countries.append(country)
    url = item.get('objectURL')
    urls.append(url)

countries

['',
 '',
 '',
 '',
 '',
 None,
 '',
 '',
 None,
 '',
 '',
 'Mali',
 '',
 '',
 None,
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 None,
 'Egypt',
 'Egypt',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 'Egypt',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 'France',
 '',
 'Egypt',
 '',
 'Egypt',
 '',
 '',
 '',
 '',
 '',
 '',
 '',
 'Turkey',
 '',
 '',
 'Byzantine Egypt',
 'Egypt',
 '',
 '',
 'Egypt',
 '',
 '',
 '',
 '',
 'Egypt',
 '',
 '',
 '',
 '',
 '',
 '',
 'Egypt',
 'Egypt',
 '',
 'Egypt',
 'Egypt',
 'Egypt',
 '',
 'Egypt',
 'Egypt',
 '',
 'Egypt',
 '',
 'Egypt',
 '',
 '',
 '',
 'Egypt']

depts

['Modern and Contemporary Art',
 'European Sculpture and Decorative Arts',
 'Greek and Roman Art',
 'Photographs',
 'Modern and Contemporary Art',
 None,
 'Modern and Contemporary Art',
 'Modern and Contemporary Art',
 None,
 'Modern and Contemporary Art',
 'Drawings and Prints',
 'The Michael C. Rockefeller Wing',
 'Modern and Contemporary Art',
 'Modern and Contemporary Art',
 None,
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Sculpture and Decorative Arts',
 'European Paintings',
 'Modern and Contemporary Art',
 None,
 'Egyptian Art',
 'Egyptian Art',
 'Greek and Roman Art',
 'Modern and Contemporary Art',
 'Medieval Art',
 'European Sculpture and Decorative Arts',
 'European Paintings',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Egyptian Art',
 'Modern and Contemporary Art',
 'European Paintings',
 'European Paintings',
 'Egyptian Art',
 'European Paintings',
 'European Paintings',
 'Greek and Roman Art',
 'Egyptian Art',
 'European Paintings',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'European Paintings',
 'European Paintings',
 'European Sculpture and Decorative Arts',
 'Drawings and Prints',
 'Modern and Contemporary Art',
 'Egyptian Art',
 'Greek and Roman Art',
 'Egyptian Art',
 'Greek and Roman Art',
 'Egyptian Art',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Greek and Roman Art',
 'Drawings and Prints',
 'Drawings and Prints',
 'Islamic Art',
 'European Paintings',
 'Modern and Contemporary Art',
 'Medieval Art',
 'Egyptian Art',
 'European Paintings',
 'European Paintings',
 'Egyptian Art',
 'European Paintings',
 'Greek and Roman Art',
 'Robert Lehman Collection',
 'European Paintings',
 'Egyptian Art',
 'European Paintings',
 'European Sculpture and Decorative Arts',
 'European Paintings',
 'Greek and Roman Art',
 'Drawings and Prints',
 'European Sculpture and Decorative Arts',
 'Egyptian Art',
 'Egyptian Art',
 'European Paintings',
 'Egyptian Art',
 'Egyptian Art',
 'Egyptian Art',
 'Robert Lehman Collection',
 'Egyptian Art',
 'Egyptian Art',
 'European Paintings',
 'Egyptian Art',
 'Greek and Roman Art',
 'Egyptian Art',
 'Modern and Contemporary Art',
 'The Cloisters',
 'Medieval Art',
 'Egyptian Art']

urls

['https://www.metmuseum.org/art/collection/search/483873',
 'https://www.metmuseum.org/art/collection/search/207162',
 'https://www.metmuseum.org/art/collection/search/247582',
 'https://www.metmuseum.org/art/collection/search/283274',
 'https://www.metmuseum.org/art/collection/search/483877',
 None,
 'https://www.metmuseum.org/art/collection/search/494305',
 'https://www.metmuseum.org/art/collection/search/481438',
 None,
 'https://www.metmuseum.org/art/collection/search/489510',
 'https://www.metmuseum.org/art/collection/search/374147',
 'https://www.metmuseum.org/art/collection/search/515811',
 'https://www.metmuseum.org/art/collection/search/492892',
 'https://www.metmuseum.org/art/collection/search/486510',
 None,
 'https://www.metmuseum.org/art/collection/search/204181',
 'https://www.metmuseum.org/art/collection/search/205376',
 'https://www.metmuseum.org/art/collection/search/193453',
 'https://www.metmuseum.org/art/collection/search/195502',
 'https://www.metmuseum.org/art/collection/search/193045',
 'https://www.metmuseum.org/art/collection/search/200897',
 'https://www.metmuseum.org/art/collection/search/208482',
 'https://www.metmuseum.org/art/collection/search/436173',
 'https://www.metmuseum.org/art/collection/search/483484',
 None,
 'https://www.metmuseum.org/art/collection/search/548584',
 'https://www.metmuseum.org/art/collection/search/551500',
 'https://www.metmuseum.org/art/collection/search/253505',
 'https://www.metmuseum.org/art/collection/search/486423',
 'https://www.metmuseum.org/art/collection/search/467700',
 'https://www.metmuseum.org/art/collection/search/196462',
 'https://www.metmuseum.org/art/collection/search/436616',
 'https://www.metmuseum.org/art/collection/search/255391',
 'https://www.metmuseum.org/art/collection/search/251428',
 'https://www.metmuseum.org/art/collection/search/547202',
 'https://www.metmuseum.org/art/collection/search/486578',
 'https://www.metmuseum.org/art/collection/search/436121',
 'https://www.metmuseum.org/art/collection/search/436896',
 'https://www.metmuseum.org/art/collection/search/547334',
 'https://www.metmuseum.org/art/collection/search/437402',
 'https://www.metmuseum.org/art/collection/search/436002',
 'https://www.metmuseum.org/art/collection/search/254469',
 'https://www.metmuseum.org/art/collection/search/560727',
 'https://www.metmuseum.org/art/collection/search/436986',
 'https://www.metmuseum.org/art/collection/search/254597',
 'https://www.metmuseum.org/art/collection/search/253135',
 'https://www.metmuseum.org/art/collection/search/249222',
 'https://www.metmuseum.org/art/collection/search/253050',
 'https://www.metmuseum.org/art/collection/search/248132',
 'https://www.metmuseum.org/art/collection/search/437099',
 'https://www.metmuseum.org/art/collection/search/436295',
 'https://www.metmuseum.org/art/collection/search/232047',
 'https://www.metmuseum.org/art/collection/search/334249',
 'https://www.metmuseum.org/art/collection/search/486845',
 'https://www.metmuseum.org/art/collection/search/544210',
 'https://www.metmuseum.org/art/collection/search/252452',
 'https://www.metmuseum.org/art/collection/search/587759',
 'https://www.metmuseum.org/art/collection/search/249091',
 'https://www.metmuseum.org/art/collection/search/547257',
 'https://www.metmuseum.org/art/collection/search/255417',
 'https://www.metmuseum.org/art/collection/search/255275',
 'https://www.metmuseum.org/art/collection/search/248689',
 'https://www.metmuseum.org/art/collection/search/389226',
 'https://www.metmuseum.org/art/collection/search/839042',
 'https://www.metmuseum.org/art/collection/search/451943',
 'https://www.metmuseum.org/art/collection/search/437881',
 'https://www.metmuseum.org/art/collection/search/486742',
 'https://www.metmuseum.org/art/collection/search/464456',
 'https://www.metmuseum.org/art/collection/search/550970',
 'https://www.metmuseum.org/art/collection/search/436024',
 'https://www.metmuseum.org/art/collection/search/437879',
 'https://www.metmuseum.org/art/collection/search/544689',
 'https://www.metmuseum.org/art/collection/search/441024',
 'https://www.metmuseum.org/art/collection/search/247004',
 'https://www.metmuseum.org/art/collection/search/459192',
 'https://www.metmuseum.org/art/collection/search/437880',
 'https://www.metmuseum.org/art/collection/search/547860',
 'https://www.metmuseum.org/art/collection/search/437160',
 'https://www.metmuseum.org/art/collection/search/231788',
 'https://www.metmuseum.org/art/collection/search/436004',
 'https://www.metmuseum.org/art/collection/search/249223',
 'https://www.metmuseum.org/art/collection/search/371017',
 'https://www.metmuseum.org/art/collection/search/196452',
 'https://www.metmuseum.org/art/collection/search/555567',
 'https://www.metmuseum.org/art/collection/search/554337',
 'https://www.metmuseum.org/art/collection/search/437390',
 'https://www.metmuseum.org/art/collection/search/546746',
 'https://www.metmuseum.org/art/collection/search/547758',
 'https://www.metmuseum.org/art/collection/search/547476',
 'https://www.metmuseum.org/art/collection/search/459052',
 'https://www.metmuseum.org/art/collection/search/547820',
 'https://www.metmuseum.org/art/collection/search/543905',
 'https://www.metmuseum.org/art/collection/search/435711',
 'https://www.metmuseum.org/art/collection/search/566713',
 'https://www.metmuseum.org/art/collection/search/255697',
 'https://www.metmuseum.org/art/collection/search/568194',
 'https://www.metmuseum.org/art/collection/search/500194',
 'https://www.metmuseum.org/art/collection/search/468716',
 'https://www.metmuseum.org/art/collection/search/466235',
 'https://www.metmuseum.org/art/collection/search/550158']

data anlaysis with pandas#

import pandas as pd

df = pd.DataFrame({
    'title': titles,
    'name': names,
    'gender': genders,
    'department': depts,
    'country': countries,
    'link': urls
})

df

	title	name	gender	department	country	link
0		Willem de Kooning		Modern and Contemporary Art		https://www.metmuseum.org/art/collection/searc...
1		Royal Porcelain Manufactory, Naples		European Sculpture and Decorative Arts		https://www.metmuseum.org/art/collection/searc...
2		Woman Painter		Greek and Roman Art		https://www.metmuseum.org/art/collection/searc...
3		Man Ray		Photographs		https://www.metmuseum.org/art/collection/searc...
4		Willem de Kooning		Modern and Contemporary Art		https://www.metmuseum.org/art/collection/searc...
...	...	...	...	...	...	...
95				Egyptian Art	Egypt	https://www.metmuseum.org/art/collection/searc...
96		Pablo Picasso		Modern and Contemporary Art		https://www.metmuseum.org/art/collection/searc...
97				The Cloisters		https://www.metmuseum.org/art/collection/searc...
98		Master of Rimini		Medieval Art		https://www.metmuseum.org/art/collection/searc...
99				Egyptian Art	Egypt	https://www.metmuseum.org/art/collection/searc...

100 rows × 6 columns

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 100 entries, 0 to 99
Data columns (total 6 columns):
 #   Column      Non-Null Count  Dtype 
---  ------      --------------  ----- 
 0   title       96 non-null     object
 1   name        96 non-null     object
 2   gender      96 non-null     object
 3   department  96 non-null     object
 4   country     96 non-null     object
 5   link        96 non-null     object
dtypes: object(6)
memory usage: 4.8+ KB

df.value_counts('department')

department
Egyptian Art                              21
European Paintings                        18
Greek and Roman Art                       18
Modern and Contemporary Art               13
European Sculpture and Decorative Arts    12
Drawings and Prints                        5
Medieval Art                               3
Robert Lehman Collection                   2
Islamic Art                                1
Photographs                                1
The Cloisters                              1
The Michael C. Rockefeller Wing            1
Name: count, dtype: int64

df.department.value_counts().plot(kind = 'barh')

<Axes: ylabel='department'>

../_images/810b06ae7dadf9ab79389810ac522118e2ab0016fb51ff889d01dbaaf8039010.png

df.department.value_counts().plot(kind = 'pie')

<Axes: ylabel='count'>

../_images/2f31712e9db59c0af4594e4c663940336f2cdd94a38e2ae5517f13212ae52ecd.png