Filter DataFrame based on dictionary values

Question

I want to filter pandas dataframe with values form dictionary .

Here is explanation.

Let's say I have dataframe like this. Data types are only string , int and timestamps .

+---------+-------+------+-------+-----------------+
|  Title  | Type  | Size | Price |      Date       |
+---------+-------+------+-------+-----------------+
| title 1 | red   |   10 |    20 | 4.9.2020. 13:21 |
| title 2 | blue  |   20 |    40 | 4.9.2020. 11:21 |
| title 3 | green |   15 |    50 | 4.5.2020. 13:21 |
+---------+-------+------+-------+-----------------+

and I have dictionary created from users input which looks like this:

  userDict =  {'Title':'title 1', 'Type':'red','Size':[10,15],'Price':[40, 80], 
    'Date':[Timestamp('2020-04-09 13:21:00'), Timestamp('2020-04-09 14:21:00')]}

'Price': [50, 80] would mean that user is requesting all prices between 50 and 80.

How can I get filtered pandas dataframe based on values from dictionary?

Original dataframe has many other columns. Besides Title and Type I could have many other string columns, and besides Size and Price I could also have many other int columns.

So dictionary can be much larger containing filtering requests for many other fields.

My solution so far:

for key, value in userDict.items():
    if 'list' in str(type(value)):
        filteredDF= originalDF[(originalDF[key] > value[0]) & (originalDF[key] < value[1])]
    if 'str' in str(type(value)):
        filteredDF= filteredDF[filteredDF[key].str.contains(value, flags=re.IGNORECASE)]

But it keeps returning original dataframe.

Answer 1

extract price value like below,

start, end = userDict["Price"]

then filter from main dataframe like below

res = df[df["Price"],between(start, end)]