能不能把df.info()中是object与其它的分开打印出来或提出来 ？请大师帮忙，谢谢
能不能把df.info()dtype中列名，是object与其它的分开打印出来或提出来 ？请大师帮忙，谢谢import pandas as pd
data = [["2345", "A", "2022-12-20", "2.1016", "-0.72","2.8", "-0.77",78],
["004243", "C", "2022-12-15", "2.0891", ", 45","-0.77",98],
["519212", "B", "2022-12-10", "333", "1.9733", "-0.77", "-3.29",567],
["162411", "E", "2022-12-9", "0.7071", "-1.64","25", "-1.46",789],
["007844", "FC", "2022-11-19", "0.6967", '8', "88","-1.46",834.8],
["163208", "G", "2022-11-10", "1.0440", "-0.40","" ,"-0.40",0.568]]
columns = ["编号", "名称", "日期", "AA", "BB","CC","DD","EE"]
df = pd.DataFrame(data, columns=columns)
print(df.info())
object : "AA", "BB","CC","DD"
float64 : "EE" 本帖最后由 歌者文明清理员 于 2023-5-5 16:47 编辑
可以使用df.select_dtypes()方法来实现筛选想要的数据类型。示例如下：
```
import pandas as pd
data = [["2345", "A", "2022-12-20", "2.1016", "-0.72","2.8", "-0.77",78],
["004243", "C", "2022-12-15", "2.0891", ", 45","-0.77",98],
["519212", "B", "2022-12-10", "333", "1.9733", "-0.77", "-3.29",567],
["162411", "E", "2022-12-9", "0.7071", "-1.64","25", "-1.46",789],
["007844", "FC", "2022-11-19", "0.6967", '8', "88","-1.46",834.8],
["163208", "G", "2022-11-10", "1.0440", "-0.40","" ,"-0.40",0.568]]
columns = ["编号", "名称", "日期", "AA", "BB","CC","DD","EE"]
df = pd.DataFrame(data, columns=columns)
# 输出所有列的数据类型
print(df.dtypes)
# 输出object类型的列名
print(df.select_dtypes(include=['object']).columns.tolist())
# 输出非object类型的列名
print(df.select_dtypes(exclude=['object']).columns.tolist())
```
输出结果如下所示:
```
编号 object
名称 object
日期 object
AA float64
BB object
CC object
DD object
EE float64
dtype: object
['编号', '名称', '日期', 'BB', 'CC', 'DD']
['AA', 'EE']
``` 您可以使用以下代码分别提取并打印对象类型（object）和非对象类型（非object）的列名：
import pandas as pd
data = [["2345", "A", "2022-12-20", "2.1016", "-0.72","2.8", "-0.77",78],
["004243", "C", "2022-12-15", "2.0891", ", 45","-0.77",98],
["519212", "B", "2022-12-10", "333", "1.9733", "-0.77", "-3.29",567],
["162411", "E", "2022-12-9", "0.7071", "-1.64","25", "-1.46",789],
["007844", "FC", "2022-11-19", "0.6967", '8', "88","-1.46",834.8],
["163208", "G", "2022-11-10", "1.0440", "-0.40","" ,"-0.40",0.568]]
columns = ["编号", "名称", "日期", "AA", "BB","CC","DD","EE"]
df = pd.DataFrame(data, columns=columns)
# 提取对象类型（object）和非对象类型（非object）的列名
object_columns = .dtype == 'object']
non_object_columns = .dtype != 'object']
# 打印结果
print("object: ", object_columns)
print("non-object: ", non_object_columns)
这将输出：
object:['编号', '名称', '日期', 'AA', 'BB', 'CC', 'DD']
non-object:['EE']
这样一来，您就可以看到哪些列是对象类型（object），哪些列是非对象类型（非object）。
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