CODEWITHSUNDEEP
pythonpandaslistdictionary
aiman khalid
aiman khalid

Reputation: 147

How to filter Data Frame based on list of dictionary?

I have 2 dictionary consist of limit values for each category of my Data Frame. These Values will not be fixed and constantly change as time goes by (monthly frequency). So my question here is, how to I filter my data frame so that each category in column ("set") will be filter according to the dictionary values.

Here is the dictionary

lower boundary
{'a': -69.79064324769809,
 'b': -4.1828456049705,
 'c': -73.1922251093512
}

upper boundary
{'a': 10.79,
 'b': 20.18,
 'c': 10.19
}

Here is the example of the data frame

set values
a     12
b     1
c     3
a     31
c     2
b     41

Here is the code that I made, but it was not dynamic and need to be manually check and replace.

df_1=df[(["set"]=="a") & (df["values"] < 10.79) & (df["values"] > -69.79064324769809)]
df_2=df[(["set"]=="b") & (df["values"] < 20.18) & (df["values"] > -4.1828456049705)]
df_3=df[(["set"]=="c") & (df["values"] < 10.19) & (df["values"] > -73.1922251093512)]

df_total=pd.concat([df_1,df_2,df_3])"

Upvotes: 0

Views: 226

Answers (1)

jezrael
jezrael

Reputation: 862691

Use Series.map for replace sets column by thresholds:

lower ={'a': -69.79064324769809,
 'b': -4.1828456049705,
 'c': -73.1922251093512
}

upper ={'a': 10.79,
 'b': 20.18,
 'c': 10.19
}

df_total=df[(df["values"] < df["set"].map(upper)) & (df["values"] > df["set"].map(lower))]
print (df_total)
  set  values
1   b       1
2   c       3
4   c       2

Or use Series.between:

df_total=df[df["values"].between(df["set"].map(lower),df["set"].map(upper),inclusive=False)]
print (df_total)
  set  values
1   b       1
2   c       3
4   c       2

Upvotes: 2

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