How to search pandas data frame by index value and value in any column
Question:
I am trying to select data, read in from a file, represented by the values one and zero. I 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. 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. Is this possible? Ultimately if another method besides pandas data frame would work better I would be willing to try that.
To be clear, any column may be selected and I do not know which ones ahead of time.
Thanks!
Answers:
You can use all() any() iloc[] operators. Check the official documentation, or this thread for more details
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})
print(df)
# You can select the value directly by using iloc[] operator
# df.iloc to select by postion .loc to Selection by Label
row_indexer,column_indexer=3,1
print(df.iloc[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])
# 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)])
I am trying to select data, read in from a file, represented by the values one and zero. I 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. 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. Is this possible? Ultimately if another method besides pandas data frame would work better I would be willing to try that.
To be clear, any column may be selected and I do not know which ones ahead of time.
Thanks!
You can use all() any() iloc[] operators. Check the official documentation, or this thread for more details
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})
print(df)
# You can select the value directly by using iloc[] operator
# df.iloc to select by postion .loc to Selection by Label
row_indexer,column_indexer=3,1
print(df.iloc[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])
# 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)])