how do I find the percent change from column X in dataframe?-CodePudding

I have a dataframe that is 49x10, and I need to find the percent change for each index item to a specific column in that row, for each index item.

Here is a sample of the dataframe being 5x10.

        -15         -10         -5          -2          -1          0           1           2           5           10          15
symbol                                          
ADS     80.098282   77.709549   72.130524   69.178314   72.947937   74.548950   75.364349   77.907074   79.691963   73.998260   67.965523
BEPC    49.635834   48.256989   45.957493   45.627144   47.968739   49.610779   48.056187   49.659355   56.013733   56.412094   59.579567
CBSH    70.400002   69.800003   70.533333   66.476189   65.250000   66.910004   66.180000   68.809998   68.089996   68.839996   68.110001
CIG     2.014711    2.097131    2.225340    2.371864    2.280286    2.089544    2.070374    2.127884    2.127884    2.204564    2.377095
CPE     12.200000   13.100000   11.800000   11.100000   10.400000   10.690000   10.050000   10.040000   8.340000    6.920000    6.630000

Essentially, I for column 0, I am trying to find the percent change centered around that date. which I have done with:

for col in df.columns:
    df[col] = (df[col] - df['0'])/df['0']*100

however, that returns a dataframe that looks like this:

        -15         -10         -5          -2          -1          0   1   2   5   10  15
symbol                                          
ADS     7.443876    4.239629    -3.244079   -7.204174   -2.147600   0.0 inf inf inf inf inf
BEPC    0.050503    -2.728823   -7.363896   -8.029777   -3.309846   0.0 inf inf inf inf inf
CBSH    5.215958    4.319234    5.415228    -0.648356   -2.480950   0.0 inf inf inf inf inf
CIG     -3.581304   0.363103    6.498839    13.511108   9.128440    0.0 inf inf inf inf inf
CPE     14.125353   22.544442   10.383542   3.835368    -2.712815   0.0 inf inf inf inf inf

The script is modifying df['0'] but I'm not sure how to find a workaround for it. The expected outcome would be percent change from df['0'], as what happened before it iterated through the 0 placement.

Any help would be appreciated.

CodePudding user response：

The answer of @nonDucor found the mistake but I would be cautious to mix percentages with absolute values. (All columns are in percentage except for column '0' which you left unchanged). To complete the answer you should update the percentages of the reference column at the end.

# Compute percentages for all non-reference columns
for col in df.columns.drop('0'):
    df[col] = (df[col] - df['0'])/df['0']*100

# Update the reference columne
df['0'] = 0.0

CodePudding user response：

Since column '0' is your reference, you should not change it (because the variation of it against itself is always 0%):

for col in df.columns:
    if col == '0':
        continue   # Skip the reference column
    df[col] = (df[col] - df['0'])/df['0']*100