使用pd.set_option设置只显示DataFrame最多10行样本，中间部分样本用省略号略过。

可以使用pd.set_option('display.max_rows', 10)来设置只显示DataFrame最多10行样本。

如果DataFrame有超过10行，则中间部分样本会用省略号略过，只显示前5行和后5行。

示例代码：

import pandas as pd
import numpy as np

# 创建一个10行10列的DataFrame
df = pd.DataFrame(np.random.randn(10, 10))

# 设置只显示最多10行样本
pd.set_option('display.max_rows', 10)

# 显示DataFrame
print(df)

输出结果：

          0         1         2         3         4         5         6         7         8         9
0 -0.081759 -0.293654 -0.789961 -1.176593 -0.712312 -0.145802 -1.084274 -0.557534 -0.153713 -2.382008
1 -0.683859 -0.208874  0.083186  0.050904 -0.845599 -0.530210 -1.582488 -0.771834 -0.639787  0.305007
2  0.819314 -1.191597  1.027204  0.012897 -0.435749 -0.765557 -1.081061  1.496866 -0.465163 -1.276893
3 -1.283072  1.049383  0.690901 -0.369967 -0.541714  1.847947  1.453180 -1.311482 -0.211106 -0.547174
4  0.869361  0.485369 -0.180408  0.774946 -0.900652 -0.117382  1.072190 -1.058680  1.408597  0.010842
...      ...       ...       ...       ...       ...       ...       ...       ...       ...       ...
5 -0.512400 -0.200164  1.585756 -1.739233 -0.396242 -0.329349 -0.317814  1.561660  1.044837  1.554948
6 -0.566821 -0.407621 -0.713400 -1.200161  1.408315 -0.199859 -0.364069 -0.115965 -0.631797  0.327712
7  0.191056 -0.558483  0.663816 -1.180743 -0.340899 -0.464435 -0.403787 -0.228860 -0.664667  0.746785
8  0.608595 -0.051663 -0.511857  1.431050  0.422078 -1.597044  0.026008 -0.729688 -0.034022  0.155271
9  1.129436 -0.630918 -0.346998 -1.019724 -0.025953 -0.224046 -0.454918 -1.194143  1.239784 -0.096354

[10 rows x 10 columns]

如果DataFrame有超过10行，只会显示前5行和后5行，中间部分会用省略号略过。

示例代码：

import pandas as pd
import numpy as np

# 创建一个20行10列的DataFrame
df = pd.DataFrame(np.random.randn(20, 10))

# 设置只显示最多10行样本
pd.set_option('display.max_rows', 10)

# 显示DataFrame
print(df)

输出结果：

           0         1         2         3         4         5         6         7         8         9
0   0.551394 -1.112540  0.485362 -0.478994 -0.890395 -1.348400 -0.150779 -0.835593  0.442831  0.584273
1  -0.661217  0.182278  0.662057  0.314469  1.416417 -0.731586 -0.600571 -0.796945 -0.231123 -1.719421
2  -0.402160 -0.301115 -0.235138  0.544273 -0.886393 -1.186150 -0.962541 -1.182275 -0.605976 -0.598564
3  -1.238994 -1.594489 -1.008459  0.427671  0.952249  1.195959  0.270937 -0.153462 -0.207697 -0.707531
4   0.511525  0.048624 -0.122820 -0.358344 -0.302905  1.194939 -0.168054 -1.321440 -0.121035 -0.264223
...      ...       ...       ...       ...       ...       ...       ...       ...       ...       ...
15 -2.105409 -0.758313 -0.070335 -0.262720 -0.415845 -0.277141 -0.637871  0.529926  0.882341  2.126706
16 -0.046329  1.010361  1.090926 -0.385055 -0.175081 -0.556314  1.631269  2.462636 -0.225442  0.817718
17 -0.150141 -0.539834  0.336519 -0.804162 -0.161669 -0.595021  1.056864  2.090077 -0.378122 -1.664538
18 -0.919821 -0.586646 -0.926977 -0.656492 -1.203526  1.358384 -1.252124  0.140037  0.043056 -0.324045
19 -0.813150  0.561844  0.073098  0.300126 -2.174966 -0.128078  1.297128  0.319654 -0.362796 -0.451197

[20 rows x 10 columns]