CODEWITHSUNDEEP
pythonpandasdataframecellmultiple-columns
Thanh Nguyen
Thanh Nguyen

Reputation: 912

Call and assign specific variables in a Pandas Dataframe

My dataset has this format, 3 columns and some unique variables

A = [A1, A2, A3, A4]
B = [B1, B2, B3]
C = [C1, C2, C3, C4, C5]

I want to call a specific variable, and then assign a value to it.

Example 1:

A     B     C
A2    B3    C5
A1    B2    C2
A3    B1    C4
A4    B2    C3
A2    B3    C1

Call all [A1, B2, C3] and assign them to be equal to [1, 2,3]

A     B     C
A2    B3    C5
1     2     C2
A3    B1    C4
A4    2     3
A2    B3    C1

@Scott Boston suggested using dictionary to assign the value in this way

Example 2: I want to assign the value one by one in a loop, such as A1 first, then do some calculation, then assign A2, and so on. Then how can I do that?

Thank you in advance

Upvotes: 2

Views: 1458

Answers (3)

DeadCoderz
DeadCoderz

Reputation: 237

For the second part of your answer I believe apply() function of pandas will be a more efficient solution. Eg:

def my_func(a):
    #your computation here

df['A'].apply(lambda x: my_func(x))

Upvotes: 0

Mukarram Pasha
Mukarram Pasha

Reputation: 368

As for your 2nd example, where you want to assign values iteratively, you an do it this way.

var = ['A1','B2','C3']
val = [1,2,3]

for i in range(len(val)):
    df = df.replace({var[i]:val[i]})
    # your calculations here...

Upvotes: 1

Scott Boston
Scott Boston

Reputation: 153500

IIUC, use replace with dictionary:

print(df)

Output:

    A   B   C
0  A2  B3  C5
1  A1  B2  C2
2  A3  B1  C4
3  A4  B2  C3
4  A2  B3  C1

Create a dictionary for replacement.

d = {'A1':1,'B2':2,'C3':3}

@Wen suggest using this statement to create dictionary:

d=dict(zip( ['A1', 'B2', 'C3'],[1,2,3] ))

df_out = df.replace(d)

print(df_out)

Output:

    A   B   C
0  A2  B3  C5
1   1   2  C2
2  A3  B1  C4
3  A4   2   3
4  A2  B3  C1

Upvotes: 4

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