Verify that a pd.Series object is iterable.

I wanted to reassure you that a pd.Series is like a Python list, but I ended up demonstrating that a pd.Series is like a Python dict.

"Iterate through a pd.Series."

import sys
import pandas as pd

data = [0.0, 10.0, 20.0, 30.0, 40.0]
series = pd.Series(data = data, name = "temperature")
print(series)
print()

print(f"{len(series) = }")
print(f"{3 in series = }")          #Is 3 in the index of the series?
print(f"{5 in series = }")          #like using in with a Python dict
print(f"{30.0 in series.array = }") #Is 30.0 in the values of the series?
print(f"{50.0 in series.array = }") #see also Series.isin
print()

#Print each float in the values column.
for f in series:
    print(f)
print()

#Print each integer in the index column.
for i in series.index:
    print(i)
print()

#Print both, in parallel.
for i, f in series.items(): #two variables, like looping through a dict using items
    print(i, f)

sys.exit(0)
0     0.0
1    10.0
2    20.0
3    30.0
4    40.0
Name: temperature, dtype: float64

len(series) = 5
3 in series = True
5 in series = False
30.0 in series.array = True
50.0 in series.array = False

0.0
10.0
20.0
30.0
40.0

0
1
2
3
4

0 0.0
1 10.0
2 20.0
3 30.0
4 40.0

Things to try

  1. Iterate through only the first three (or only the last three) items in the Series. series[:3] is a slice of the Series.
    for i, f in series[:3].items():   #also try series[-3:]
        print(i, f)
    
    0 0.0
    1 10.0
    2 20.0
    
  2. Iterate through every other item in the Series.
    for i, f in series[::2].items():
        print(i, f)
    
    0 0.0
    2 20.0
    4 40.0
    
  3. Iterate backwards. Can’t use the Python reversed function.
    for i, f in series[::-1].items():
        print(i, f)
    
    4 40.0
    3 30.0
    2 20.0
    1 10.0
    0 0.0