Pandas Pct_change Gives Slightly Different Answers To Manual

Can anyone explain why the pct_change function gives slightly different numbers when using the more manual calculation: pct_change function: print(prices) 0

Solution 1:

Problem is second formula is wrong:

prices = pd.DataFrame({0:[1035.23,1032.47]})
print (prices)

print(prices.pct_change(1))
          0
0       NaN
1 -0.002666

print(prices/(prices.shift())-1)
          0
0       NaN
1 -0.002666

As pointed Andrew L in comment:

print((prices - prices.shift(1))/prices.shift(1))
          0
0       NaN
1 -0.002666