前言

提示：文章数据来自kaggle，还发现了https://sofifa.com/这个牛的不得了的网站。

从Kaggle下载了fifa dataset（2015年~2022年），做些分析和可视化练习，分多些篇目来记录吧，争取上半年能完成。

Kaggle上有两篇可以参考学习：
1、https://www.kaggle.com/code/stefanoleone992/fifa-22-players-lineup-visualization-and-more
2、https://www.kaggle.com/code/brightezeoha/fifa-22-data-analysis

一、目标

先做几个简单的：
1、统计球员总数以及每年数量变化情况（新增、退役）
2、球员综合指标变化
3、在综合指标上增加球员价值变化
4、按国家、按年龄、按球员位置统计人数
再来两个难的：
1、综合来看，哪项指标最容易提升
2、综合得分80分以上的球员通常具备什么特质（区分位置），这些特质通常是什么年龄段形成的。

二、步骤

1.处理数据

先定义es索引template，字段太多，挑几个用到的定义下：

{"template": "fifa-players-*","settings": {"index": {"number_of_shards": "5","number_of_replicas": "1"},"analysis":{   "analyzer":{"ik":{"tokenizer":"ik_max_word"}}}},"mappings": {"properties": {"sofifa_id": {"type": "keyword"},"player_url": {"type": "keyword"},"overall": {"type": "keyword"},"potential": {"type": "keyword"},"value_eur": {"type": "keyword"},"wage_eur": {"type": "keyword"},"dob": {"type": "keyword"},"club_name": {"type": "keyword"},"club_position": {"type": "keyword"},"nationality_name": {"type": "keyword"}}},"aliases": {}
}

用logstash把几个csv导入到es里。csv2es.conf文件如下，每个csv导入到一个索引里：

input {file {path => "E:/kaggle/works/dataset/players_15.csv"start_position => "beginning"}
}
filter {csv {separator => ","columns => ["sofifa_id","player_url","short_name","long_name","player_positions","overall","potential","value_eur","wage_eur","age","dob","height_cm","weight_kg","club_team_id","club_name","league_name","league_level","club_position","club_jersey_number","club_loaned_from","club_joined","club_contract_valid_until","nationality_id","nationality_name","nation_team_id","nation_position","nation_jersey_number","preferred_foot","weak_foot","skill_moves","international_reputation","work_rate","body_type","real_face","release_clause_eur","player_tags","player_traits","pace","shooting","passing","dribbling","defending","physic","attacking_crossing","attacking_finishing","attacking_heading_accuracy","attacking_short_passing","attacking_volleys","skill_dribbling","skill_curve","skill_fk_accuracy","skill_long_passing","skill_ball_control","movement_acceleration","movement_sprint_speed","movement_agility","movement_reactions","movement_balance","power_shot_power","power_jumping","power_stamina","power_strength","power_long_shots","mentality_aggression","mentality_interceptions","mentality_positioning","mentality_vision","mentality_penalties","mentality_composure","defending_marking_awareness","defending_standing_tackle","defending_sliding_tackle","goalkeeping_diving","goalkeeping_handling","goalkeeping_kicking","goalkeeping_positioning","goalkeeping_reflexes","goalkeeping_speed","ls","st","rs","lw","lf","cf","rf","rw","lam","cam","ram","lm","lcm","cm","rcm","rm","lwb","ldm","cdm","rdm","rwb","lb","lcb","cb","rcb","rb","gk","player_face_url","club_logo_url","club_flag_url","nation_logo_url","nation_flag_url"]}
}
output {elasticsearch {hosts => "http://127.0.0.1:9200"index => "fifa-players-2015"}
}

2.构造ES语句

1、统计球员总数以及每年数量变化情况（新增、退役）
如下，docs.count列代表球员总数。

# curl -H "Content-Type: application/json"  http://127.0.0.1:9200/_cat/indices?v | grep fifa
health status index                              uuid                   pri rep docs.count docs.deleted store.size pri.store.size
yellow open fifa-players-2015                  lbXuWKBdRqSTDxHSeVPGGQ 5 1   16155  0  41.9mb  41.9mb
yellow open fifa-players-2016                  IDYQNqXvSVmpMuoKSRWGhw 5 1   15623  0  40.5mb  40.5mb
yellow open fifa-players-2017                  LdlLQSEGSd6XniAScT5PpA 5 1   17596  0  47.3mb  47.3mb
yellow open fifa-players-2018                  lU2cC2FHRBOsQlqWYfkF1g 5 1   17954  0  48.2mb  48.2mb
yellow open fifa-players-2019                  wvmoBDSxT9-pAogAVfhqUg 5 1   18085  0  48.8mb  48.8mb
yellow open fifa-players-2022                  GyE3v6oZQ9GvLPH-9zcUBg 5 1   19239  0  51.7mb  51.7mb
yellow open fifa-players-2020                  omp_E0VKRRGFsPTFZ63kHg 5 1   18483  0    50mb    50mb
yellow open fifa-players-2021                  mXz8Gi24QmOI3pW9PL-W7Q 5 1   18944  0  50.8mb  50.8mb

总结

今天就做了处理数据，搭开发环境，部署生产环境。
生产环境地址：http://apr.kunmtech.com

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【Kaggle】FIFA球员数据可视化分析（一）

文章目录

前言

一、目标

二、步骤

1.处理数据

2.构造ES语句

总结

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