如何按索引值和任何列中的值搜索熊猫数据框

Question

我正在尝试选择数据，从文件中读取，由值 1 和 0 表示。我希望能够从值列表中选择行，同时选择每个选定行的值为 1 的任何列。为了使其更复杂，我还想从值列表中选择行，其中这些行的列中的所有值都为零。这可能吗？最终，如果除了 pandas 数据框之外的另一种方法会更好，我愿意尝试。

需要明确的是，可以选择任何列，我不知道提前哪些列。

谢谢！

Answer 1

您可以使用 all() any() ix[] 运算符。查看official documentation或this thread了解更多详情

import pandas as pd
import random
import numpy as np


#created a dump data as you didn't provide one
df = pd.DataFrame({'col1':  [random.getrandbits(1) for i in range(10)], 'col2':  [random.getrandbits(1) for i in range(10)], 'col3': [1]*10})

#You can select the value directly by using ix[] operator
row_indexer,column_indexer=3,1
print df.ix[row_indexer,column_indexer]

#You can filter the data of a specific column this way
print df[df['col1']==1]
print df[df['col2']==1]

#df.iloc to select by postion .loc to  Selection by Label

#want to be able to select rows from a list of values and at the same time select for any column in which each of the selected rows has a value of one.
print df[(df.T == 1).any()]
# if you wanna filter a specific columns with a condition on rows
print df[(df['col1']==1)|(df['col2']==1)]
#To make it more complex I also want to select rows from a list of values where all values in a column for these rows is zero.
print df[(df.T == 0).all()]
# if you wanna filter a specific columns with a condition on rows
print df[(df['col1']==0) & (df['col2']==0)]