I would like to plot two columns of a dataframe against one column. The values in these columns are a wide range of numbers.

data = {'A': [ -0.9, -0.5, -0.3, -0.1, 0, 0.2, 0.4, 0.5, 0.8, 0.9,], 'B': [0, 0, 17, 59, 243, 6777, 35531, 909876, 3, 8], 'C': [7312, 22434, 10787, 4576, 25, 0, 5, 12, 0, 32]}

[I have put the numbers are in an order in the example, to show that the values of B against the values of A vs the values of C against the values of C, but they need not be.]

df = pd.DataFrame(data)

df.plot(x='A', y='B', kind='line')
df.plot(x='A', y='C', kind='line')

Since the range of numbers is large, I cannot see the smaller numbers distinctively. I tried using log numbers, but because there are zeros, I am not able to do that.

What is the best way to plot this data on a single graph and see clear difference between values of B & C against values of A?
I am trying to find a pattern here, as shown in the example where if A <0 C values are high and if A >0 B values are high.