我试图通过以下方式找到每篇文章的主导主题:Lda_model是模型，语料库由id2word.doc2bow(text)组成，文本是应用模型的文本数据。
def format_topics_sentences(ldamodel=lda_model, corpus=corpus, texts=data):
# Init output
sent_topics_df = pd.DataFrame()
# Get main topic in each document
for i, row in enumerate(ldamodel[corpus]):
row = sorted(row, key=lambda x: (x[1]), reverse=True)
# Get the Dominant topic, Perc Contribution and Keywords for each document
for j, (topic_num, prop_topic) in enumerate(row):
if j == 0: # => dominant topic
wp = ldamodel.show_topic(topic_num)
topic_keywords = ", ".join([word for word, prop in wp])
sent_topics_df = sent_topics_df.append(pd.Series([int(topic_num), round(prop_topic,4), topic_keywords]), ignore_index=True)
else:
break
sent_topics_df.columns = ['Dominant_Topic', 'Perc_Contribution', 'Topic_Keywords']
# Add original text to the end of the output
contents = pd.Series(texts)
sent_topics_df = pd.concat([sent_topics_df, contents], axis=1)
return(sent_topics_df)
df_topic_sents_keywords = format_topics_sentences(ldamodel=optimal_model, corpus=corpus, texts=data)
# Format
df_dominant_topic = df_topic_sents_keywords.reset_index()
df_dominant_topic.columns = ['Document_No', 'Dominant_Topic', 'Topic_Perc_Contrib', 'Keywords', 'Text']
# Show
df_dominant_topic.head(10)
对于下面的块，我似乎得到了错误:
for i, row in enumerate(model_gr[corpus][0:1]):
print(row)
row = sorted(row, key=lambda x: (x[1]), reverse=True)
出现以下错误:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Input In [186], in <cell line: 1>()
1 for i, row in enumerate(lda_model_gr[corpus]):
2 print(row)
----> 3 row = sorted(row, key=lambda x: (x[1]), reverse=True)
TypeError: '<' not supported between instances of 'int' and 'tuple'
如果这个错误能被解决，那将会很有帮助。打印(行)产生:
([(5, 0.28596485), (6, 0.16911359), (8, 0.030976538), (10, 0.011954311), (11, 0.068368636), (13, 0.34729925), (15, 0.016343366), (17, 0.05741114)], [(0, [6, 11]), (1, [5]), (2, [5]), (3, [6, 5]), (4, [13, 6, 5, 11, 10]), (5, [13, 5, 17, 10, 15, 19]), (6, [5, 13, 11, 17]), (7, [5, 13, 11]), (8, [5, 13, 17, 10]), (9, [5, 13, 8, 6, 17]), (10, [13, 6, 5, 11, 17, 10]), (11, [13, 6, 5, 11, 10, 17, 15, 16, 19]), (12, [5, 13, 11, 19, 10]), (13, [5, 13]), (14, [8]), (15, [13, 5, 11, 10]), (16, [6]), (17, [13, 5, 19, 11]), (18, [11, 13, 19]), (19, [5]), (20, [5, 13]), (21, [13, 6, 11, 15, 19]), (22, [13, 17, 6, 15, 11, 10, 19]), (23, [5, 11, 13, 16, 15]), (24, [5, 13, 6, 15, 19]), (25, [6, 5, 13]), (26, [6, 5, 13, 15]), (27, [11, 6]), (28, [13, 5, 17, 15, 11, 19]), (29, [17, 10, 13]), (30, [13, 6, 5, 10, 15]), (31, [6, 5, 13, 11]), (32, [5, 11]), (33, [5]), (34, [13, 10, 5, 11, 17, 6, 16]), (35, [5, 17, 13, 11]), (36, [5]), (37, []), (38, [6, 13, 5, 11]), (39, [13, 8]), (40, [13, 8]), (41, [10, 5, 13]), (42, [13, 5, 11, 6]), (43, []), (44, [6, 16, 19]), (45, [5, 6, 11]), (46, [5, 13]), (47, [5, 19, 11]), (48, [13, 15]), (49, [13, 15]), (50, [5]), (51, [5, 17]), (52, []), (53, [13, 6, 5, 2]), (54, []), (55, [6, 13, 11, 10]), (56, [13, 5]), (57, [11]), (58, [15]), (59, [5, 15, 16]), (60, [6]), (61, [6, 13, 5, 11, 17, 10]), (62, [17, 13, 8, 15, 10]), (63, [8]), (64, [13, 6, 15, 19, 11]), (65, [6]), (66, [5, 13]), (67, [13, 17, 5]), (68, [6, 13, 5, 11, 19, 10]), (69, [5, 13, 17]), (70, [13, 5, 11, 15, 10, 17]), (71, [13, 6, 11, 15, 19, 10]), (72, [17, 15, 19, 11, 10, 13, 16]), (73, [6, 5]), (74, [5, 17, 13, 11]), (75, []), (76, [11, 13, 5, 17, 10, 6, 19]), (77, [13]), (78, [5, 13, 17, 6, 15, 10]), (79, [13, 5, 6, 11, 19]), (80, [6]), (81, [5, 13, 11, 17, 19]), (82, [6, 13, 11, 8]), (83, [13, 6, 11, 5]), (84, [11, 13, 17, 15]), (85, [6, 8, 13, 17, 10]), (86, [13, 17, 19, 10]), (87, [5]), (88, [17, 13, 6, 11]), (89, [5, 13]), (90, [13, 5, 8, 19]), (91, []), (92, [6, 17]), (93, [6, 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0.39435294), (19, 0.034823406)]), (199, [(13, 0.96775484), (19, 0.022879016)]), (200, [(5, 0.50008476), (13, 0.13684608), (17, 1.3437235), (19, 0.019204019)]), (201, [(5, 0.28973544), (6, 0.6771141), (19, 0.030683247)]), (202, [(5, 0.72740936), (6, 0.70894116), (11, 0.08029629), (13, 0.46888885)]), (203, [(5, 0.9990135)]), (204, [(13, 0.10984679), (17, 0.8860627)]), (205, []), (206, [(5, 2.1814685), (10, 0.010261451), (13, 0.10968065), (17, 0.6919027)]), (207, [(5, 1.6329234), (11, 0.16604121), (13, 0.09986477), (19, 0.09936662)]), (208, []), (209, []), (210, [(6, 0.98902684), (10, 0.010309203)]), (211, [(5, 0.8766025), (10, 0.025843045), (11, 0.15526077), (13, 0.9418555)]), (212, []), (213, [(13, 0.99704975)]), (214, [(5, 0.99885416)]), (215, [(5, 0.21299508), (6, 0.7658666), (10, 0.020584367)]), (216, [(6, 0.6826777), (10, 0.012727588), (11, 0.2534499), (13, 0.034274943), (16, 0.012877893)]), (217, [(5, 0.11966399), (6, 1.3196429), (10, 0.020960262), (11, 0.015896216), (13, 0.50265044), (15, 0.020670826)]), (218, [(5, 2.2757893), (6, 1.3534186), (10, 0.029892182), (11, 0.13136972), (13, 0.20872839)]), (219, [(5, 0.3468926), (6, 0.6506149)]), (220, [(5, 1.8485144), (13, 0.14501871)]), (221, [(5, 0.25912252), (6, 0.17810631), (8, 0.24370039), (10, 0.037707243), (11, 0.20553175), (13, 0.07483299)]), (222, [(5, 0.7876651), (13, 2.1635923), (16, 0.015844675), (19, 0.028262476)]), (223, [(5, 1.0295696), (6, 1.5752087), (10, 0.07156202), (11, 0.2412992), (13, 2.0537336), (16, 0.012706131)]), (224, []), (225, [(13, 0.9998467)]), (226, [(5, 0.19591874), (6, 1.0906304), (10, 0.1905979), (11, 0.105449244), (13, 3.1307368), (15, 0.06470487), (17, 0.20054035), (19, 0.018632406)]), (227, [(6, 0.9987916)]), (228, [(5, 0.97771984), (16, 0.0218728)]), (229, [(5, 0.99859655)]), (230, [(5, 0.6475402), (6, 0.32668734), (11, 0.02392782)]), (231, [(6, 0.1344872), (11, 1.1646075), (13, 0.7007387)]), (232, [(8, 0.10104955), (10, 0.030233635), (11, 0.06184386), (13, 0.59889644), (15, 0.046360116), (17, 0.13581054), (19, 0.025584122)]), (233, [(5, 0.40037483), (6, 0.14609358), (10, 0.027402246), (13, 0.41244912)]), (234, [(8, 0.019712333), (19, 0.9443963)]), (235, [(5, 0.10418052), (6, 0.6320547), (11, 0.2169608), (13, 0.033399854), (19, 0.010283742)]), (236, [(5, 0.9959411)]), (237, [(5, 0.23990116), (6, 1.7178776), (10, 0.034481186)]), (238, [(8, 0.14724466), (13, 1.850922)]), (239, []), (240, [(6, 0.8977852), (15, 0.09624253)]), (241, [(6, 0.025402123), (8, 0.90599746), (11, 0.06850036)]), (242, [(5, 0.547783), (6, 0.28439674), (10, 0.014434091), (13, 0.13190828), (15, 0.0142463455)]), (243, [(6, 0.13199379), (10, 0.057886217), (11, 0.044038814), (13, 0.7375677), (16, 0.01539999), (19, 0.012251117)]), (244, [(17, 0.9888149)]), (245, [(5, 1.2593493), (8, 0.12706786), (11, 0.2334989), (13, 0.3034959), (17, 0.07299953)]), (246, []), (247, [(8, 0.018343199), (10, 0.069553435), (11, 0.3669271), (13, 0.34456688), (17, 0.19741665)]), (248, [(5, 0.5976373), (10, 0.018292593), (13, 0.38294467)]), (249, [(5, 0.18479073), (6, 0.6413081), (11, 0.38013488), (13, 0.35495862), (15, 0.03424214), (17, 0.40325254)]), (250, [(6, 0.08034917), (11, 1.9176077)]), (251, [(5, 0.20393085), (6, 0.78029704), (11, 0.014970283)]), (252, [(5, 0.64575917), (13, 0.022136863), (15, 0.0187605), (17, 0.30664405)]), (253, [(5, 1.442483), (11, 0.16993758), (13, 0.83663845), (17, 0.5453098)]), (254, [(5, 0.35664973), (11, 0.14691326), (13, 0.19329375), (17, 0.2940971)]), (255, []), (256, [(5, 0.41977447), (6, 0.117519066), (11, 0.060630452), (13, 0.39950612)]), (257, [(5, 1.1185334), (6, 0.6945151), (13, 0.18598245)]), (258, [(6, 0.7178949), (17, 0.27780265)]), (259, [(5, 0.2315536), (6, 1.2198883), (11, 0.3824548), (13, 0.15637466)]), (260, [(5, 0.7238699), (6, 4.682581), (11, 0.40098134), (13, 1.1820863)]), (261, [(6, 0.95957875), (11, 0.040013768)]), (262, [(5, 1.015397), (10, 0.06664863), (13, 0.9090345)]), (263, [(5, 0.47510156), (6, 0.49131647), (11, 0.03326682)]), (264, [(5, 0.2209457), (6, 0.44723123), (11, 0.21056525), (13, 0.0959901), (15, 0.020397339)]), (265, [(13, 1.9956943)]), (266, [(6, 0.3809251), (10, 0.014788828), (13, 0.38318476), (17, 0.22062777)]), (267, [(5, 0.029857425), (6, 0.9402752), (10, 0.02590593)]), (268, [(5, 0.64380306), (13, 0.34743822)]), (269, [(5, 0.11750559), (6, 0.8823499)]), (270, [(6, 0.44937772), (11, 0.5390605), (15, 0.011173154)]), (271, [(11, 0.2647513), (13, 0.7337882)]), (272, [(5, 0.26731408), (10, 0.030186307), (13, 1.643601), (17, 0.04851736)]), (273, [(11, 0.25765947), (13, 0.6533741), (19, 0.08843155)]), (274, [(5, 2.0963056), (6, 0.017009757), (13, 1.8549889), (19, 0.029400624)]), (275, [(5, 0.27814716), (13, 4.7212873)]), (276, [(5, 3.3794577), (6, 0.35977948), (13, 2.2527797)]), (277, [(10, 0.022175033), (11, 0.40720117), (13, 2.1680253), (17, 0.40236053)]), (278, [(11, 0.09760688), (13, 0.8362114), (15, 0.020611858), (19, 0.040899552)]), (279, [(5, 0.50572246), (10, 0.025718477), (11, 0.039611906), (13, 1.3801457), (19, 0.04631573)]), (280, [(5, 0.14597909), (11, 0.8513083)]), (281, [(5, 0.48851472), (8, 0.5101291)]), (282, []), (283, [(5, 1.9939348), (6, 0.44371378), (11, 0.103731446), (13, 0.45728233)]), (284, [(5, 1.4199508), (10, 0.03615384), (17, 0.5426531)]), (285, [(5, 0.8740896), (6, 0.12192376)]), (286, [(5, 0.40902787), (6, 1.3055351), (8, 0.21426035), (11, 0.011262591), (13, 0.047578946), (16, 0.010891321)]), (287, [(5, 1.8233716), (8, 0.17567201)]), (288, [(5, 0.09208407), (6, 0.6540262), (10, 0.015362142), (11, 0.03480859), (13, 0.10554817), (17, 0.09803497)]), (289, [(13, 0.8756386), (15, 0.11996283)]), (290, [(8, 0.9914311)]), (291, [(5, 0.52997047), (6, 0.32427138), (10, 0.02762359), (13, 0.117458716)]), (292, [(5, 0.121682875), (6, 0.9736432), (13, 0.8890763)]), (293, [(5, 0.95656765), (13, 1.7425864), (17, 0.2989374)]), (294, []), (295, [(11, 0.26136807), (13, 0.7278068)]), (296, [(5, 0.7181937), (6, 2.721199), (10, 0.016427245), (11, 0.08950079), (13, 0.41189432), (15, 0.032551423)]), (297, [(5, 0.542341), (6, 0.46200514), (11, 0.32819828), (13, 0.60858375), (19, 0.05845866)]), (298, [(6, 0.60774845), (8, 0.058460683), (11, 0.020373259), (13, 0.3131928)]), (299, [(5, 2.1014476), (8, 1.6672884), (13, 0.23035948)]), (300, [(11, 0.017025072), (13, 0.9675423)]), (301, [(13, 0.9309519), (17, 0.06890718)]), (302, [(5, 1.3083501), (6, 0.40939847), (11, 0.04729645), (13, 0.23426363)]), (303, [(8, 0.9910873)]), (304, [(6, 0.362415), (11, 0.05419311), (13, 0.5763127)]), (305, [(5, 0.99957144)]), (306, [(6, 0.8227331), (10, 0.067680344), (11, 0.10437946)]), (307, [(5, 1.2720524), (6, 0.61079097), (11, 0.01399885), (13, 0.082511365)]), (308, [(13, 0.99104434)]), (309, [(15, 0.017685179), (17, 1.9443939), (19, 0.03626969)]), (310, [(5, 0.9182231), (13, 0.081057556)]), (311, [(5, 0.27469856), (11, 0.077621914), (13, 0.5723921), (17, 0.06384972)]), (312, [(11, 0.9375039), (15, 0.052889265)]), (313, [(5, 0.26359212), (13, 0.70027715), (19, 0.034536064)]), (314, [(5, 0.2868577), (6, 0.33469313), (10, 0.013444621), (11, 0.028426826), (13, 0.333877)]), (315, [(5, 0.23929082), (8, 0.24916436), (10, 0.053220075), (11, 0.3889066), (13, 0.050798014), (17, 0.011353827)]), (316, [(13, 0.857545), (17, 0.14135489)]), (317, [(5, 0.29502746), (6, 0.5368782), (11, 0.08066518), (13, 0.0864927)]), (318, [(8, 0.85062176), (11, 0.5525968), (13, 0.79487807), (17, 0.80160546)]), (319, [(5, 5.760585), (8, 0.20784947), (10, 0.06649702), (13, 0.8233435), (17, 0.14133)]), (320, []), (321, [(15, 0.8437948)]), (322, [(5, 0.08627563), (6, 0.8453305), (10, 0.027926847), (11, 0.03973386)]), (323, [(5, 1.7549213), (13, 0.24465045)]), (324, []), (325, [(5, 0.23698263), (17, 0.76168483)]), (326, [(5, 0.9412229), (8, 0.015167902), (10, 0.06843942), (13, 0.82948655), (17, 0.13536783)]), (327, [(5, 0.5699474), (6, 2.3699284), (10, 0.016917715), (11, 0.061381046), (13, 1.91574), (15, 0.05792646)]), (328, [(8, 0.9131497), (9, 0.048321426)]), (329, []), (330, [(5, 0.80192566), (17, 0.19617847)]), (331, [(13, 5.362196), (15, 0.12975213), (17, 3.5078437)]), (332, [(5, 0.5936004), (10, 0.021148894), (13, 0.044429537), (17, 0.3357255)]), (333, [(5, 0.056643162), (6, 0.9235007), (13, 0.019360073)]), (334, [(5, 0.23667754), (6, 1.7632058)]), (335, [(5, 0.2927878), (6, 0.6749614), (10, 0.03172394)]), (336, [(5, 0.037975095), (6, 0.24890976), (10, 0.01476361), (13, 0.5511085), (15, 0.034392715), (17, 0.103100955)]), (337, [(5, 0.2744202), (8, 0.56620514), (13, 7.1583757)]), (338, [(11, 0.99053866)]), (339, [(5, 0.9992218)]), (340, [(5, 0.9999391)]), (341, [(5, 0.39050665), (6, 0.46527576), (11, 0.03496145), (13, 0.108623475)]), (342, [(5, 0.61833644), (10, 0.015222529), (13, 0.10572725), (17, 0.2338722), (19, 0.019023256)]), (343, [(15, 0.928358)]), (344, [(8, 1.199619), (13, 0.799196)]), (345, [(13, 0.9962762)]), (346, [(16, 0.9200263)]), (347, [(5, 2.1576533), (6, 0.08436395), (13, 0.95397663), (17, 0.7777478), (19, 0.014683125)]), (348, [(15, 1.8959556)]), (349, [(5, 0.30803165), (17, 0.691142)]), (350, [(19, 0.6248793)]), (351, [(5, 3.3922043), (10, 0.05677398), (13, 0.19132452), (17, 0.35881528)]), (352, [(5, 1.1335676), (6, 0.4307446), (13, 0.41215315), (15, 0.012671193)]), (353, [(6, 0.99875885)]), (354, [(5, 0.3504603), (6, 0.30245423), (10, 0.014050029), (11, 0.038248967), (13, 0.2535254), (15, 0.02151125), (17, 0.014715961)]), (355, [(6, 0.9978003)]), (356, [(8, 0.6938963), (11, 0.20359914), (13, 0.092883095)]), (357, [(5, 0.3649056), (6, 0.63446707)]), (358, [(5, 0.30298933), (6, 0.31410143), (13, 0.34828243), (15, 0.024025684)]), (359, [(2, 0.01208612), (5, 0.49561238), (6, 0.44600818), (13, 3.842865), (15, 0.0686453), (17, 0.13172367)]), (360, [(5, 1.7383987), (6, 3.6478453), (10, 0.079790324), (11, 2.616148), (13, 3.7626178), (15, 0.11112045), (19, 0.040238842)])])
您的数据被阻塞了。
用),n替换),，并手动添加一些缩进，输入的前几行看起来像这样:
(
[
(5, 0.28596485),
(6, 0.16911359),
(8, 0.030976538),
(10, 0.011954311),
(11, 0.068368636),
(13, 0.34729925),
(15, 0.016343366),
(17, 0.05741114)
],
[
(0, [6, 11]),
(1, [5]),
(2, [5]),
(3, [6, 5]),
之后你有
[
(0, [(6, 0.5968742), (11, 0.39671573)]),
(1, [(5, 0.9998293)]),
(2, [(5, 0.99847865)]),
(3, [(5, 0.4248721),
所以x[1]似乎可以是一个元组，一个列表，或元组的列表…?
也许可以试着检查一下:
print({type(x[1]) for x in row})
(提示:最好用代码编辑你的问题，因为注释会破坏任何格式)
由于所有的x[1]都是元组，您可能有类似的情况:
>>> lst = [
... (1, 2),
... (1, (2,3)),
... ]
>>> print({type(x) for x in lst})
{<class 'tuple'>}
>>> sorted(lst)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: '<' not supported between instances of 'tuple' and 'int'
>>>
，因为元组比较比较每个单独的项。这肯定会更有挑战性……也许:
def get_tuple_type(tpl):
"Return a tuple of the types of individual tuple elements."
return tuple([type(item) for item in tpl])
types = {get_tuple_type(row[0][1])} # initialize with the type of the first element
for x in row:
xtype = get_tuple_type(x[1])
if xtype not in types:
print(f'offending value: {x!r} has type {xtype!r} - not any of {types!r}')
如果您找到兼容(但不严格相等)的类型，您可以手动将它们复制到types集并再次运行，直到找到问题值。