如何从从 excel 文件派生的大量字典中的值列表中查找最小值和最大值

Question

I am new with dealing dictionary and Pandas in Python. I have a excel file with columns named sensor and values, sensors can be duplicates also, but their values can differ. I converted them into dictionary merging duplicate sensors with their values. Now, I have a dictionary with sensors and their values as list (example given below). I want to return all the keys with the lowest and highest value from their list of values. Values can be duplicate also.

{'Sensor1': [0.427, 0.13, 0.129, 0.124], 'sensor2': [2.376, 2.376, 0.712, 0.618.208, 0.133], 'sensor3': [0.21, 0.139], 'sensor4': [0.237, 0.123], 'sensor5': [0.997, 0.806, 6.78]}

I want the output to be

sensor1 0.124 0.427
sensor2 0.133 2.376
sensor3 0.139 0.21
.
.
.

The code that I have tried is giving me only first set of key,value pair ie

senor1 0.124 0.427

code -

df = pd.read_excel("sensor.xlsx")
a=df.set_index('sensor')['values'].to_dict()
b={k: g["values"].to_list() for k,g in df.groupby("sensor")}
for k,v in b.items():
    _max, _min = max(v), min(v)
    print(k, " ", _min, " ",  _max)

My excel file is large and this code is not working for that. Please help, Thanks in Advance!

Answer 1

In you already have the dictionary then you can just load the data into the dataframe and evaluate min/max across axis = 1 .

data = {'Sensor1': [0.427, 0.13, 0.129, 0.124], 'sensor2': [2.376, 2.376, 0.712, 0.618208, 0.133], 'sensor3': [0.21, 0.139], 'sensor4': [0.237, 0.123], 'sensor5': [0.997, 0.806, 6.78]}

df = pd.DataFrame.from_dict(data, orient='index') 
df = pd.concat([df.min(1) , df.max(1)], axis =1)

Or you can use:

df = df.agg(['min', 'max'], axis='columns')  # suggested by @Cyttorak 

OUTPUT

            0      1
Sensor1  0.124  0.427
sensor2  0.133  2.376
sensor3  0.139  0.210
sensor4  0.123  0.237
sensor5  0.806  6.780

If you want to convert the above output back to dict :

result = df.T.to_dict('list')