我有一个文本文件,该文件有9列和许多行(大约30k)。它的某些行的前五列中的条目可以具有相同的值。在这种情况下,我想将它们转换为单行,其中第6-8列的条目中的值为平均值。如果一行是唯一的,那么我想按原样打印。我的原始文件如下所示。
6nbn A 18 49 A 1.82270650408 2.03219831709 1.82706048066 1
6nbn A 45 98 A 1.82498684927 2.03457366541 1.82271363631 1
6nbn A 88 107 A 1.82115046056 2.03480564182 1.82785940378 1
6nbn A 18 49 A 1.81906074665 2.03189099117 1.82705062875 2
6nbn A 45 98 A 1.82562290739 2.03479384705 1.82313137212 2
6nbn A 88 107 A 1.82279510642 2.03515331118 1.82660203657 2
6nbn A 18 49 A 1.82147248126 2.03104332795 1.82474573571 3
6nbn A 45 98 A 1.82470216748 2.03683136268 1.82329893325 3
6nbn A 88 107 A 1.82258525178 2.0307116979 1.8247273769 3
8tfv A 11 18 A 1.81042122171 2.01948136906 1.80238314462 1
8tfv A 11 18 A 1.80688488842 2.02074367499 1.8064168954 2
8tfv A 11 18 A 1.80874790947 2.02178955384 1.80609219034 3
8tfv A 11 18 A 1.80850988385 2.01873277082 1.80290765155 4
8tfv A 11 18 A 1.80312229203 2.01855121312 1.80927195302 5
8t11 B 1 4 A 1.80874790947 2.02178955384 1.80609219034 1
而且我想要这样的输出文件:
6nbn A 18 49 A 1.82107991066 2.03171087874 1.82628561504
6nbn A 45 98 A 1.82510397471 2.03539962505 1.82304798056
6nbn A 88 107 A 1.82217693958 2.03355688363 1.82639627242
8tfv A 11 18 A 1.80753723909 2.01985971637 1.80541436699
8t11 B 1 4 A 1.80874790947 2.02178955384 1.80609219034
我是python编程的新手。如果您能帮助我解决这个问题,我将为您提供很大的帮助。
尝试一下(用列名替换数字):
df.groupby(['0','1','2','3','4'])['5','6','7'].mean()
5 6 7
0 1 2 3 4
6nbn A 18 49 A 1.821080 2.031711 1.826286
45 98 A 1.825104 2.035400 1.823048
88 107 A 1.822177 2.033557 1.826396
8t11 B 1 4 A 1.808748 2.021790 1.806092
8tfv A 11 18 A 1.807537 2.019860 1.805414
import pandas as pd
from io import StringIO
data = StringIO("""
6nbn A 18 49 A 1.82270650408 2.03219831709 1.82706048066 1
6nbn A 18 49 A 1.81906074665 2.03189099117 1.82705062875 2
6nbn A 45 98 A 1.82562290739 2.03479384705 1.82313137212 2
""")
df = pd.read_csv(data, sep=' ', engine='python', names=['a','b','c','d','e','f','g','h','i'])
result = df.groupby(['a','b','c','d','e']).agg('mean')
输出:
f g h i
a b c d e
6nbn A 18 49 A 1.820884 2.032045 1.827056 1.5
45 98 A 1.825623 2.034794 1.823131 2.0