学习目标
- 目标
- 了解Pandas的几种文件读取存储操作
- 应用CSV方式、HDF方式和json方式实现文件的读取和存储
我们的数据大部分存在于文件当中,所以pandas会支持复杂的IO操作,pandas的API支持众多的文件格式,如CSV、SQL、XLS、JSON、HDF5。
注:最常用的HDF5和CSV文件
1 CSV
1.1 read_csv
- pandas.read_csv(filepath_or_buffer, sep =’,’, usecols )
- filepath_or_buffer:文件路径
- sep :分隔符,默认用”,”隔开
- usecols:指定读取的列名,列表形式
举例:读取之前的股票的数据
# 读取文件,并且指定只获取'open', 'close'指标
data = pd.read_csv("./data/stock_day.csv", usecols=['open', 'close'])
open close
2018-02-27 23.53 24.16
2018-02-26 22.80 23.53
2018-02-23 22.88 22.82
2018-02-22 22.25 22.28
2018-02-14 21.49 21.92
1.2 to_csv
DataFrame.to_csv(path_or_buf=None, sep=’, ’, columns=None, header=True, index=True, mode=’w’, encoding=None)
- path_or_buf :文件路径
- sep :分隔符,默认用”,”隔开
- columns :选择需要的列索引
- header :boolean or list of string, default True,是否写进列索引值
- index:是否写进行索引
- mode:’w’:重写, ‘a’ 追加
举例:保存读取出来的股票数据
保存’open’列的数据,然后读取查看结果
# 选取10行数据保存,便于观察数据
data[:10].to_csv("./data/test.csv", columns=['open'])
# 读取,查看结果
pd.read_csv("./data/test.csv")
Unnamed: 0 open
0 2018-02-27 23.53
1 2018-02-26 22.80
2 2018-02-23 22.88
3 2018-02-22 22.25
4 2018-02-14 21.49
5 2018-02-13 21.40
6 2018-02-12 20.70
7 2018-02-09 21.20
8 2018-02-08 21.79
9 2018-02-07 22.69
会发现将索引存入到文件当中,变成单独的一列数据。如果需要删除,可以指定index参数,删除原来的文件,重新保存一次。
# index:存储不会讲索引值变成一列数据
data[:10].to_csv("./data/test.csv", columns=['open'], index=False)
2 HDF5
2.1 read_hdf与to_hdf
HDF5文件的读取和存储需要指定一个键,值为要存储的DataFrame
pandas.read_hdf(path_or_buf,key =None,** kwargs)从h5文件当中读取数据
- path_or_buffer:文件路径
- key:读取的键
- return:Theselected object
DataFrame.tohdf(path_or_buf, _key, __kwargs)
2.2 案例
读取文件
day_close = pd.read_hdf("./data/day_close.h5")
如果读取的时候出现以下错误
需要安装安装tables模块避免不能读取HDF5文件pip install tables
存储文件
day_close.to_hdf("./data/test.h5", key="day_close")
再次读取的时候, 需要指定键的名字
new_close = pd.read_hdf("./data/test.h5", key="day_close")
注意:优先选择使用HDF5文件存储
HDF5在存储的时候支持压缩,使用的方式是blosc,这个是速度最快的也是pandas默认支持的
- 使用压缩可以提磁盘利用率,节省空间
-
3 JSON
JSON是我们常用的一种数据交换格式,前面在前后端的交互经常用到,也会在存储的时候选择这种格式。所以我们需要知道Pandas如何进行读取和存储JSON格式。
3.1 read_json
pandas.read_json(path_or_buf=None, orient=None, typ=’frame’, lines=False)
- 将JSON格式准换成默认的Pandas DataFrame格式
- orient : string,Indication of expected JSON string format.
- ‘split’ : dict like {index -> [index], columns -> [columns], data -> [values]}
- split 将索引总结到索引,列名到列名,数据到数据。将三部分都分开了
- ‘records’ : list like [{column -> value}, … , {column -> value}]
- records 以columns:values的形式输出
- ‘index’ : dict like {index -> {column -> value}}
- index 以index:{columns:values}…的形式输出
- ‘columns’ : dict like {column -> {index -> value}},默认该格式
- colums 以columns:{index:values}的形式输出
- ‘values’ : just the values array
- values 直接输出值
- ‘split’ : dict like {index -> [index], columns -> [columns], data -> [values]}
- lines : boolean, default False
- 按照每行读取json对象
- typ : default ‘frame’, 指定转换成的对象类型series或者dataframe
3.2 read_josn 案例
数据介绍
这里使用一个新闻标题讽刺数据集,格式为json。is_sarcastic:1讽刺的,否则为0;headline:新闻报道的标题;article_link:链接到原始新闻文章。存储格式为:
{"article_link": "https://www.huffingtonpost.com/entry/versace-black-code_us_5861fbefe4b0de3a08f600d5", "headline": "former versace store clerk sues over secret 'black code' for minority shoppers", "is_sarcastic": 0}
{"article_link": "https://www.huffingtonpost.com/entry/roseanne-revival-review_us_5ab3a497e4b054d118e04365", "headline": "the 'roseanne' revival catches up to our thorny political mood, for better and worse", "is_sarcastic": 0}
- 读取
orient指定存储的json格式,lines指定按照行去变成一个样本
json_read = pd.read_json("./data/Sarcasm_Headlines_Dataset.json", orient="records", lines=True)
3.3 to_json
DataFrame.tojson(_path_or_buf=None, orient=None, lines=False)
存储文件
json_read.to_json("./data/test.json", orient='records')
结果
[{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/versace-black-code_us_5861fbefe4b0de3a08f600d5","headline":"former versace store clerk sues over secret 'black code' for minority shoppers","is_sarcastic":0},{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/roseanne-revival-review_us_5ab3a497e4b054d118e04365","headline":"the 'roseanne' revival catches up to our thorny political mood, for better and worse","is_sarcastic":0},{"article_link":"https:\/\/local.theonion.com\/mom-starting-to-fear-son-s-web-series-closest-thing-she-1819576697","headline":"mom starting to fear son's web series closest thing she will have to grandchild","is_sarcastic":1},{"article_link":"https:\/\/politics.theonion.com\/boehner-just-wants-wife-to-listen-not-come-up-with-alt-1819574302","headline":"boehner just wants wife to listen, not come up with alternative debt-reduction ideas","is_sarcastic":1},{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/jk-rowling-wishes-snape-happy-birthday_us_569117c4e4b0cad15e64fdcb","headline":"j.k. rowling wishes snape happy birthday in the most magical way","is_sarcastic":0},{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/advancing-the-worlds-women_b_6810038.html","headline":"advancing the world's women","is_sarcastic":0},....]
修改lines参数为True
json_read.to_json("./data/test.json", orient='records', lines=True)
结果
{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/versace-black-code_us_5861fbefe4b0de3a08f600d5","headline":"former versace store clerk sues over secret 'black code' for minority shoppers","is_sarcastic":0}
{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/roseanne-revival-review_us_5ab3a497e4b054d118e04365","headline":"the 'roseanne' revival catches up to our thorny political mood, for better and worse","is_sarcastic":0}
{"article_link":"https:\/\/local.theonion.com\/mom-starting-to-fear-son-s-web-series-closest-thing-she-1819576697","headline":"mom starting to fear son's web series closest thing she will have to grandchild","is_sarcastic":1}
{"article_link":"https:\/\/politics.theonion.com\/boehner-just-wants-wife-to-listen-not-come-up-with-alt-1819574302","headline":"boehner just wants wife to listen, not come up with alternative debt-reduction ideas","is_sarcastic":1}
{"article_link":"https:\/\/www.huffingtonpost.com\/entry\/jk-rowling-wishes-snape-happy-birthday_us_569117c4e4b0cad15e64fdcb","headline":"j.k. rowling wishes snape happy birthday in the most magical way","is_sarcastic":0}...
4 小结
pandas的CSV、HDF5、JSON文件的读取【知道】
- 对象.read_**()
- 对象.to_**()