关于#python#的问题：可以提供一个适用于以下代码的微博情感分析数据集嘛

可以提供一个适用于以下代码的微博情感分析数据集嘛？要运行这些代码需要安装哪些库？
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd
from keras.models import *
from keras.layers import *
from keras.models import Model
from keras.layers import LSTM, Dense, Dropout, Input, Embedding
from keras.preprocessing.text import Tokenizer
from keras.preprocessing import sequence
import jieba
data =pd.read_excel(r'C:\Users\86139\Desktop\review_4_cut.xlsx')
data['review'] = data['review'].astype(str)
data['fenci'] = data['fenci'].astype(str)
#训练集
train_0=data[data['label']==0][:50000]
train_1=data[data['label']==1][:50000]
train_2=data[data['label']==2][:50000]
train_3=data[data['label']==3][:50000]
train= pd.concat([train_0,train_1,train_2,train_3],ignore_index=True)
#稳定集
val_0=data[data['label']==0][50000:51000]
val_1=data[data['label']==1][50000:51000]
val_2=data[data['label']==2][50000:51000]
val_3=data[data['label']==3][50000:51000]
val=pd.concat([val_0,val_1,val_2,val_3],ignore_index=True)
#测试集
test_0=data[data['label']==0][51000:51500]
test_1=data[data['label']==1][51000:51500]
test_2=data[data['label']==2][51000:51500]
test_3=data[data['label']==3][51000:51500]
test=pd.concat([test_0,test_1,test_2,test_3],ignore_index=True)
data_1=pd.concat([train,val,test],ignore_index=True)
max_len=100
max_words=5000 #最大词语数量
tok_1=Tokenizer(num_words=max_words)#序列化
tok_1.fit_on_texts(data_1.fenci)
train_seq=tok_1.texts_to_sequences(train.fenci)
val_seq=tok_1.texts_to_sequences(val.fenci)
test_seq=tok_1.texts_to_sequences(test.fenci)
#序列化,长度一致
train_seq_mat=sequence.pad_sequences(train_seq,maxlen=max_len)
val_seq_mat=sequence.pad_sequences(val_seq,maxlen=max_len)
test_seq_mat=sequence.pad_sequences(test_seq,maxlen=max_len)
from keras.preprocessing import sequence
from sklearn.preprocessing import LabelEncoder,OneHotEncoder
train_y=train.label #标签结果
val_y=val.label
test_y=test.label #标签
le=LabelEncoder()#文本转化为数字
train_y=le.fit_transform(train_y).reshape(-1,1)
val_y=le.fit_transform(val_y).reshape(-1,1)
test_y=le.fit_transform(test_y).reshape(-1,1)
ohe=One....(后面还有代码就不一一复制了)

需要安装哪些库？import下的库都需要安装
pandas matplotlib seaborn numpy

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import pandas as pd

https://gitee.com/baidu/Senta?_from=gitee_search
百度有情感分析的开源项目，且提供相应的数据集下载，不知道对你有没有帮助，
微博的情感分析还需要对应你的代码的就太难了