Update examples

Author: Michael-E-Rose

docs/classes/SerialTitle.rst

@@ -29,15 +29,15 @@ You can obtain basic information just by printing the object:
 .. code-block:: python
 
     >>> print(source)
-    'Science', journal published by 'American Association for the Advancement of Science', is active in Multidisciplinary and Medicine (all)
-    Metrics as of 2023-04-03:
+    'Science', journal published by 'American Association for the Advancement
+    of Science', is active in Multidisciplinary
+    Metrics as of 2023-11-15:
         SJR:  year value
-              2021 14.589
+              2022 13.328
         SNIP: year value
-              2021 9.116
+              2022 7.729
         ISSN: 0036-8075, E-ISSN: 1095-9203, Scopus ID: 23571
 
-
 The object has a number of attributes but no methods.  For example, information regarding the source itself:
 
 .. code-block:: python
@@ -59,30 +59,54 @@ Most importantly, it provides three metrics: the CiteScore (see `here <https://s
 .. code-block:: python
 
     >>> source.citescoreyearinfolist
-    [(2021, 57.8), (2022, 57.3)]
+    [Citescoreinfolist(year=2022, citescore=59.0),
+     Citescoreinfolist(year=2023, citescore=58.8)]
     >>> source.sjrlist
-    [(2021, 14.589)]
+    [(2022, 13.328)]
     >>> source.sniplist
-    [(2021, 9.116)]
+    [(2022, 7.729)]
+
 
+Property `citescoreyearinfolist` can return detailed information for all available years with `view="CITESCORE"`. It includes the status of the metric, the document count and citation count (of the previous 4 years), the share of documents actually cited, and the rank and percentile for each related ASJC subject:
+
+.. code-block:: python
 
-The only longer time series is provide in paramter `yearly_data`. It contains the number of documents published in this year, the share of review articles thereof, the number and share of not-cited documents, and the number of distinct documents that were cited in this year.
+    >>> source_full = SerialTitle("00368075", view="CITESCORE")
+    >>> info = pd.DataFrame(source_full.citescoreyearinfolist)
+    >>> print(info)
+        year  citescore       status  documentcount  citationcount  percentcited                             rank
+    0   2023       58.8  In-Progress           4730         278199            79                  [(1000, 2, 99)]
+    1   2022       59.0     Complete           4895         288748            82                  [(1000, 2, 98)]
+    2   2021       57.8     Complete           4823         278545            84                  [(1000, 2, 98)]
+    3   2020       46.8     Complete           4833         226134            82                  [(1000, 2, 98)]
+    4   2019       45.3     Complete           4799         217261            81                  [(1000, 2, 98)]
+    5   2018       47.1     Complete           4681         220642            82                  [(1000, 2, 98)]
+    6   2017       49.4     Complete           4215         208286            90                  [(1000, 2, 98)]
+    7   2016       49.5     Complete           4176         206665            89                  [(1000, 1, 99)]
+    8   2015       46.6     Complete           4016         187040            89  [(2700, 18, 99), (1000, 2, 98)]
+    9   2014       46.0     Complete           3923         180376            90  [(2700, 18, 99), (1000, 2, 98)]
+    10  2013       46.9     Complete           3839         179860            92  [(2700, 16, 99), (1000, 2, 98)]
+    11  2012       46.3     Complete           3861         178780            92  [(2700, 11, 99), (1000, 2, 98)]
+    12  2011       44.7     Complete           3843         171898            91  [(2700, 12, 99), (1000, 2, 98)]
+
+
+Another time series is `yearly_data`. It contains the number of documents published in this year, the share of review articles thereof, the number and share of not-cited documents, and the number of distinct documents that were cited in this year.
 
 
 .. code-block:: python
 
     >>> source.yearly_data[-1]
-    Yearlydata(year=2023, publicationcount=0, revpercent=0.0,
-               zerocitessce=0, zerocitespercentsce=None, citecountsce=30145)
+    Yearlydata(year=2023, publicationcount=1800, revpercent=2.94,
+               zerocitessce=1201, zerocitespercentsce=66.72222222222223,
+               citecountsce=726948)
     >>> yearly_data = pd.DataFrame(source.yearly_data)
     >>> yearly_data.head()
        year  publicationcount  revpercent  zerocitessce  zerocitespercentsce  citecountsce
-    0  1996              2395        4.97           661            27.599165        235971
-    1  1997              2833        6.28           905            31.944935        243521
-    2  1998              2816        4.69           855            30.362216        253994
-    3  1999              2373        6.28           534            22.503161        275590
-    4  2000              2401        7.00           462            19.241983        293442
-
+    0  1996              2395        4.97           655            27.348643        236545
+    1  1997              2833        6.28           904            31.909636        244078
+    2  1998              2816        4.69           854            30.326705        254500
+    3  1999              2373        6.28           532            22.418879        276054
+    4  2000              2402        6.99           459            19.109076        293867
 
 
 By default, `SerialTitle()` retrieves only the most recent metrics while yearly data is availble from 1996 onwards.  If you provide a year or a range of years via the optional parameter `years`, `SerialTitle()` will retrieve information for these years (except for the CiteScore):
@@ -91,7 +115,8 @@ By default, `SerialTitle()` retrieves only the most recent metrics while yearly
 
     >>> source_y = SerialTitle("00368075", years="2017-2019")
     >>> source_y.citescoreyearinfolist
-    [(2020, 46.8), (2021, 51.9)]
+    [Citescoreinfolist(year=2022, citescore=59.0),
+     Citescoreinfolist(year=2023, citescore=58.8)]
     >>> source_y.sjrlist
     [(2017, 14.142), (2018, 13.251), (2019, 13.11)]
     >>> source_y.sniplist