How to query Pandas df based on row values and column header with Python

Question

Is there a way to query the df based on the row values and column header? Looking to pass through Disney , World , and Value as variables to return 55 . I tried using the df.loc function but received errors. The Key1 and Key2 headers are set as the df.index .

Pandas Dataframe

Key1	Key2	Value
Disney	World	55
Disney	Land	97

Answer 1

如果 key1 和 key2 作为多索引在索引中，我认为你只需要这个。

df.loc[('Disney', 'World'), 'Value']

Answer 2

You can get values of 'Value' to with this code

pd.read_csv(PATH)
data = data.dropna()
Value = data['Value'].values # Get values of 'Value'
# Key2 = data['Key2'].values # Get values of 'Key2'
print(Value)

And output will be

[55, 97]

Answer 3

IIUC, you create a function, pass the parameters and get the value in return

df=df.set_index(['Key1', 'Key2'])

def findval(df, Key1, Key2):
    return df.loc[(Key1, Key2), 'Value']

findval(df, 'Disney', 'Land')

RESULT:

97

OR

def findval(df, Key1, Key2):
    return df[(df['Key1'] == Key1) & 
              (df['Key2'] == Key2)]['Value']

findval(df, 'Disney', 'Land')

1 97
Name: Value, dtype: int64

Answer 4

只需直接在系列上发出多索引表达式：

df.Value['Disney', 'World']