Divide a value in a Dataframe column with the previous value in the same column

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I'm working with pandas and dataframe, and I have a simple question:

I have a dataframe (let's call it df) like this:

index A B C
0 3 2 5
1 4 7 6
2 2 4 8

i need to make an additional column D, in with I must have the ratio of the C Value with the precedent one: first value of the column should be 5/0 (where impossible to divide, NAN or 0 will be good), second value should be 6/5, third value should be 8/6.

I can't manage to make it work. I'm trying to apply lambda function but without success when it comes to use the "previous value". (.shift() is not working)

df['D'] = df['C'].apply(lambda x:x['C']/ ???   )

Is this the right road, or there is something I am missing?

pandas dataframe division python
1 Answers

Use Series.shift instead of apply:

df['D'] = df['C'] / df['C'].shift()

# index  A  B  C         D
# 0      3  2  5       NaN
# 1      4  7  6  1.200000
# 2      2  4  8  1.333333

Optionally chain Series.fillna if you want 0 instead of NaN:

df['D'] = df['C'].div(df['C'].shift()).fillna(0)

# index  A  B  C         D
# 0      3  2  5  0.000000
# 1      4  7  6  1.200000
# 2      2  4  8  1.333333
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