DataFrame loc vs. iloc
locby values (here we start from the row where the index column == 3ilocby index (here we start from the 3rd row)
import sys
import pandas as pd
filename = "planets.csv"
if len(sys.argv) == 2:
filename = sys.argv[1]
df = pd.read_csv(filename)
print(df)
print()
print(df.loc[3:6]) # by values (here we start from the row where the index column == 3
print()
print(df.iloc[3:6]) # by index (here we start from the 3rd row)
print()
sorted_df = df.sort_values('Planet name', ascending=True)
print(sorted_df)
print()
print(sorted_df.loc[3:6])
print()
print(sorted_df.iloc[3:6])
print()
print('-------')
print(sorted_df.loc[2:4])
print()
print(sorted_df.iloc[2:4])
print()
Output:
Planet name Distance (AU) Mass
0 Mercury 0.40 0.055000
1 Venus 0.70 0.815000
2 Earth 1.00 1.000000
3 Mars 1.50 0.107000
4 Ceres 2.77 0.000150
5 Jupiter 5.20 318.000000
6 Saturn 9.50 95.000000
7 Uranus 19.60 14.000000
8 Neptune 30.00 17.000000
9 Pluto 39.00 0.002180
10 Charon 39.00 0.000254
Planet name Distance (AU) Mass
3 Mars 1.50 0.10700
4 Ceres 2.77 0.00015
5 Jupiter 5.20 318.00000
6 Saturn 9.50 95.00000
Planet name Distance (AU) Mass
3 Mars 1.50 0.10700
4 Ceres 2.77 0.00015
5 Jupiter 5.20 318.00000
Planet name Distance (AU) Mass
4 Ceres 2.77 0.000150
10 Charon 39.00 0.000254
2 Earth 1.00 1.000000
5 Jupiter 5.20 318.000000
3 Mars 1.50 0.107000
0 Mercury 0.40 0.055000
8 Neptune 30.00 17.000000
9 Pluto 39.00 0.002180
6 Saturn 9.50 95.000000
7 Uranus 19.60 14.000000
1 Venus 0.70 0.815000
Planet name Distance (AU) Mass
3 Mars 1.5 0.10700
0 Mercury 0.4 0.05500
8 Neptune 30.0 17.00000
9 Pluto 39.0 0.00218
6 Saturn 9.5 95.00000
Planet name Distance (AU) Mass
5 Jupiter 5.2 318.000
3 Mars 1.5 0.107
0 Mercury 0.4 0.055
-------
Empty DataFrame
Columns: [Planet name, Distance (AU), Mass]
Index: []
Planet name Distance (AU) Mass
2 Earth 1.0 1.0
5 Jupiter 5.2 318.0