How to properly apply filters in pandas from the given set of filters?-CodePudding

I am having trouble applying filters with pandas. The problem looks like this. The first variable in the set (filter_names) should correspond to the first variable in the set (filter_values). The value of the second variable should be bigger or equal to the value given. In other words, in the input like this:

df = pd.DataFrame({'animal': ['cat', 'cat', 'snake', 'dog', 'dog', 'cat', 'snake', 'cat', 'dog', 'dog'],
                   'age': [2.5, 3, 0.5, np.nan, 5, 2, 4.5, np.nan, 7, 3],
                   'name': ['Murzik', 'Pushok', 'Kaa', 'Bobik', 'Strelka', 'Vaska', 'Kaa2', 'Murka', 'Graf', 'Muhtar'],
                   'visits': [1, 3, 2, 3, 2, 3, 1, 1, 2, 1],
                   'priority': ['yes', 'yes', 'no', 'yes', 'no', 'no', 'no', 'yes', 'no', 'no']},
                 index = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'])
filter_names = ["animal", "age"]
filter_values = ["cat", 3]

the condition to be put in the query looks like this: "cat"=="animal", "age"<3.

It should provide the DF below:


  animal  age    name  visits priority
a    cat  2.5  Murzik       1      yes
f    cat  2.0   Vaska       3       no

I wrote the following code to achieve this effect:

df_filtered = df[(filter_names[0]==filter_values[0])&(df[filter_names[1]]>=filter_values[1])]

to no avail. What do I seem to be missing?

CodePudding user response：

I think you lost df[...]in the first condition and use the wrong sign in the second one:

df[(df[filter_names[0]] == filter_values[0]) & (df[filter_names[1]] < filter_values[1])]

It will work like this:

In [2]: df[(df[filter_names[0]] == filter_values[0]) & (df[filter_names[1]] < filter_values[1])]
Out[2]: 
  animal  age    name  visits priority
a    cat  2.5  Murzik       1      yes
f    cat  2.0   Vaska       3       no