import pandas as pd
# Read csv data from file
wideCrimesDF = pd.read_csv('Crime.csv')
wideCrimesDF.shape
wideCrimesDF.head()
Offence State 2000 2001 2002 2003 ...
0 Homicide NSW 262 313 256 233 ...
1 Assault NSW 68,714 75,461 80,028 79,890 ...
2 Sexual assault NSW 5,975 6,268 6,477 6,799 ...
3 Kidnapping NSW 385 470 435 421 ...
4 Robbery NSW 13,328 15,234 11,707 10,849 ...
5 rows × 25 columns
# Convert data to long format
crimesDF = pd.melt(wideCrimesDF, id_vars = ['Offence','State'], var_name = 'Year', value_name = 'Count')
crimesDF.head()
Offence State Year Count
0 Homicide NSW 2000 262
1 Assault NSW 2000 68,714
2 Sexual assault NSW 2000 5,975
3 Kidnapping NSW 2000 385
4 Robbery NSW 2000 13,328
crimesDF.shape
