pandas.DataFrame: companies
Info
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 77096 entries, 0 to 77095
Data columns (total 5 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 id 77096 non-null int64
1 company_rating 47187 non-null object
2 company_location 57966 non-null object
3 total_fleet_count 77089 non-null float64
4 iata_approved 77089 non-null object
dtypes: float64(1), int64(1), object(3)
memory usage: 2.9+ MB
Table Head
id company_rating company_location total_fleet_count iata_approved
0 35029 100% Niue 4.00 f
1 30292 67% Anguilla 6.00 f
2 19032 67% Russian Federation 4.00 f
3 8238 91% Barbados 15.00 t
4 30342 NaN Sao Tome and Principe 2.00 t
Table Tail
id company_rating company_location total_fleet_count iata_approved
77091 6654 100% Tonga 3.00 f
77092 8000 NaN Chile 2.00 t
77093 14296 NaN Netherlands 4.00 f
77094 27363 80% NaN 3.00 t
77095 12542 98% Mauritania 19.00 t
Describe
id total_fleet_count
count 77,096.00 77,089.00
mean 25,155.39 30.47
std 14,300.99 165.55
min 1.00 1.00
25% 12,935.75 1.00
50% 25,253.50 1.00
75% 37,410.25 4.00
max 50,098.00 1,484.00
NaN counts
id 0
company_rating 29909
company_location 19130
total_fleet_count 7
iata_approved 7
Unique Values
id 50098
company_rating 70
company_location 181
total_fleet_count 90
iata_approved 2