假设您具有以下条件
Dataframe：
编辑
我检查了文档，您可能应该使用
pandas.set_optionAPI来做到这一点：
In [13]: dfOut[13]: a b c0 4.405544e+08 1.425305e+08 6.387200e+081 8.792502e+08 7.135909e+08 4.652605e+072 5.074937e+08 3.008761e+08 1.781351e+083 1.188494e+07 7.926714e+08 9.485948e+084 6.071372e+08 3.236949e+08 4.464244e+085 1.744240e+08 4.062852e+08 4.456160e+086 7.622656e+07 9.790510e+08 7.587101e+087 8.762620e+08 1.298574e+08 4.487193e+088 6.262644e+08 4.648143e+08 5.947500e+089 5.951188e+08 9.744804e+08 8.572475e+08In [14]: pd.set_option('float_format', '{:f}'.format)In [15]: dfOut[15]: a b c0 440554429.333866 142530512.999182 638719977.8249651 879250168.522411 713590875.479215 46526045.8194872 507493741.709532 300876106.387427 178135140.5835413 11884941.851962 792671390.499431 948594814.8166474 607137206.305609 323694879.619369 446424361.5220715 174424035.448168 406285189.907148 445616045.7541376 76226556.685384 979050957.963583 758710090.1278677 876261954.607558 129857447.076183 448719292.4535098 626264394.999419 464814260.796770 594750038.7475959 595118819.308896 974480400.272515 857247528.610996In [16]: df.describe()Out[16]:a b ccount 10.000000 10.000000 10.000000mean 479461624.877280 522785202.100082 536344333.626082std 306428177.277935 320806568.078629 284507176.411675min 11884941.851962 129857447.076183 46526045.81948725% 240956633.919592 306580799.695412 445818124.69612150% 551306280.509214 435549725.351959 521734665.60055275% 621482597.825966 772901261.744377 728712562.052142max 879250168.522411 979050957.963583 948594814.816647编辑结束
In [7]: dfOut[7]: a b c0 4.405544e+08 1.425305e+08 6.387200e+081 8.792502e+08 7.135909e+08 4.652605e+072 5.074937e+08 3.008761e+08 1.781351e+083 1.188494e+07 7.926714e+08 9.485948e+084 6.071372e+08 3.236949e+08 4.464244e+085 1.744240e+08 4.062852e+08 4.456160e+086 7.622656e+07 9.790510e+08 7.587101e+087 8.762620e+08 1.298574e+08 4.487193e+088 6.262644e+08 4.648143e+08 5.947500e+089 5.951188e+08 9.744804e+08 8.572475e+08In [8]: df.describe()Out[8]: a b ccount 1.000000e+01 1.000000e+01 1.000000e+01mean 4.794616e+08 5.227852e+08 5.363443e+08std 3.064282e+08 3.208066e+08 2.845072e+08min 1.188494e+07 1.298574e+08 4.652605e+0725% 2.409566e+08 3.065808e+08 4.458181e+0850% 5.513063e+08 4.355497e+08 5.217347e+0875% 6.214826e+08 7.729013e+08 7.287126e+08max 8.792502e+08 9.790510e+08 9.485948e+08
您需要摆弄
pandas.options.display.float_format属性。请注意，在我的代码中我使用了
import pandas aspd。快速修复是这样的：
In [29]: pd.options.display.float_format = "{:.2f}".formatIn [10]: dfOut[10]: a b c0 440554429.33 142530513.00 638719977.821 879250168.52 713590875.48 46526045.822 507493741.71 300876106.39 178135140.583 11884941.85 792671390.50 948594814.824 607137206.31 323694879.62 446424361.525 174424035.45 406285189.91 445616045.756 76226556.69 979050957.96 758710090.137 876261954.61 129857447.08 448719292.458 626264395.00 464814260.80 594750038.759 595118819.31 974480400.27 857247528.61In [11]: df.describe()Out[11]: a b ccount 10.00 10.00 10.00mean 479461624.88 522785202.10 536344333.63std 306428177.28 320806568.08 284507176.41min 11884941.85 129857447.08 46526045.8225% 240956633.92 306580799.70 445818124.7050% 551306280.51 435549725.35 521734665.6075% 621482597.83 772901261.74 728712562.05max 879250168.52 979050957.96 948594814.82
