Fortune-1000列舉了全美1000間最大公司，sector(領域)從零售業、科技、能源、金融、健康照護等，數據包括revenue、profit、員工人數、女性ceo人數等。能從Fortune-1000得到全美revenue、profit與產業領域、員工人數的相關性。此外，女性ceo在各領域的比例也能從fortune-1000的資料中得到。
data可以從Fortune.com取得[1]，此dataset在kaggle上也能輕易下載下來進行分析[2]。非常謝謝kaggle上有前人分析整理並提供程式碼，研究到一篇bronze獎的分析，大幅加速自己對資料分析的認識與基礎[3]。
RangeIndex: 1000 entries, 0 to 999
Data columns (total 18 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 company 1000 non-null object
1 rank 1000 non-null int64
2 rank_change 1000 non-null float64
3 revenue 1000 non-null float64
4 profit 997 non-null float64
5 num. of employees 999 non-null float64
6 sector 1000 non-null object
7 city 1000 non-null object
8 state 1000 non-null object
9 newcomer 1000 non-null object
10 ceo_founder 1000 non-null object
11 ceo_woman 1000 non-null object
12 profitable 1000 non-null object
13 prev_rank 1000 non-null object
14 CEO 1000 non-null object
15 Website 1000 non-null object
16 Ticker 951 non-null object
17 Market Cap 969 non-null object
dtypes: float64(4), int64(1), object(13)
memory usage: 140.8+ KB
None
Index: 996 entries, 0 to 999
Data columns (total 18 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 company 996 non-null object
1 rank 996 non-null int64
2 rank_change 996 non-null float64
3 revenue 996 non-null float64
4 profit 996 non-null float64
5 num. of employees 996 non-null float64
6 sector 996 non-null object
7 city 996 non-null object
8 state 996 non-null object
9 newcomer 996 non-null bool
10 ceo_founder 996 non-null bool
11 ceo_woman 996 non-null bool
12 profitable 996 non-null bool
13 prev_rank 996 non-null object
14 ceo 996 non-null object
15 website 996 non-null object
16 ticker 996 non-null object
17 market cap 966 non-null object
dtypes: bool(4), float64(4), int64(1), object(9)
memory usage: 120.6+ KB
None
company rank rank_change revenue profit num. of employees \
249 Lam Research 250 54.0 14626.2 3908.5 14100.0
sector city state newcomer ceo_founder ceo_woman profitable \
249 Technology Fremont CA False False False True
prev_rank ceo website ticker \
249 304.0 Timothy M. Archer https://www.lamresearch.com LRCX
market cap
249 74996.7
company False
rank False
rank_change False
revenue False
profit False
num. of employees False
sector False
city False
state False
newcomer False
ceo_founder False
ceo_woman False
profitable False
prev_rank False
ceo False
website False
ticker False
market cap True
dtype: bool
state company_count
3 CA 131
40 TX 97
31 NY 86
13 IL 62
32 OH 54
35 PA 45
8 FL 38
42 VA 34
9 GA 34
18 MA 33
21 MI 30
25 NC 29
22 MN 27
29 NJ 23
5 CT 23
39 TN 22
23 MO 21
45 WI 21
4 CO 21
2 AZ 20
sector ceo_woman
16 Retailing 14
6 Financials 12
4 Energy 9
9 Health Care 9
17 Technology 7
0 Aerospace & Defense 4
11 Household Products 4
13 Materials 4
12 Industrials 4
18 Transportation 2
10 Hotels, Restaurants & Leisure 2
8 Food, Beverages & Tobacco 2
7 Food & Drug Stores 2
2 Business Services 2
1 Apparel 1
14 Media 1
15 Motor Vehicles & Parts 1
5 Engineering & Construction 1
3 Chemicals 1
19 Wholesalers 1
Next: Visualization
| company | profit | revenue | ceo_woman | ceo | |
|---|---|---|---|---|---|
| 43 | Citigroup | 21952.0 | 79865.0 | True | Jane Fraser |
| 90 | Oracle | 13746.0 | 40479.0 | True | Safra A. Catz |
| 33 | United Parcel Service | 12890.0 | 97287.0 | True | Carol B. Tomé |
| 24 | General Motors | 10019.0 | 127004.0 | True | Mary T. Barra |
| 3 | CVS Health | 7910.0 | 292111.0 | True | Karen Lynch |
| sector | profit | |
|---|---|---|
| 6 | Financials | 556635.2 |
| 17 | Technology | 459503.3 |
| 9 | Health Care | 209442.4 |
| 4 | Energy | 139828.6 |
| 16 | Retailing | 126835.7 |
