Use Python to convert the data types of all columns in dataframe format to categorical data types

1. Sample understanding

import pandas as pd
import numpy as np

# 创建测试数据
feature_names = ['col1 ', 'col2', 'col3', 'col4', 'col5', 'col6']
values = np.random.randint(20, size=(10,6))

dataset = pd.DataFrame(data = values, columns = feature_names)

print("转换前的数据为\n",dataset)
print(dataset.dtypes)

print("======================================================")

# 获取dataframe格式数据的特征名称
feature_names = list(dataset)
print("特征名称为\n",feature_names)

# 将特征值转为分类数据
for col in feature_names:
    dataset[col] = dataset[col].astype('category',copy=False)

print("转换后的数据为\n",dataset)
print(dataset.dtypes)

2. Dataframe format data sample description

import pandas as pd
import numpy as np
test1 = pd.read_csv('./test.csv',encoding='utf-8',index_col=0)
test1

# 获取特征名称
features = [x for x in test3.columns if x not in ['pos','LABEL']]

#将特征数据类型转换为分类数据
for col in features:
    test2[col] = test2[col].astype('category',copy=False)