Python数据分析——Pandas（5）

学习目标

目标
- 了解Pandas的几种文件读取存储操作
- 应用CSV方式和HDF方式实现文件的读取和存储
应用
- 实现股票数据的读取存储

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 =',' )
- filepath_or_buffer:文件路径
- usecols:指定读取的列名，列表形式

读取之前的股票的数据

# 读取文件,并且指定只获取'最高价', '最低价'指标
data = pd.read_csv("./600690.csv", usecols=['最高价', '最低价'])

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 :string or file handle, default None
- sep :character, default ‘,’
- columns :sequence, optional
- mode:'w'：重写, 'a' 追加
- index:是否写进行索引
- header :boolean or list of string, default True,是否写进列索引值

1.3 案例

保存'open'列的数据

# 选取10行数据保存,便于观察数据
data[:10].to_csv("./test.csv", columns=['最高价'])

读取，查看结果

pd.read_csv("./test.csv")

注意文件编码为UTF-8

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("./test.csv", columns=['最高价'], 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.to_hdf(path_or_buf, key, *\kwargs*)

2.2 案例

读取文件

day_eps_ttm = pd.read_hdf("./data/test.h5")

如果读取的时候出现以下错误：

"No module named 'tables' " problem importing

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_eps_ttm.to_hdf("./data/test.h5", key="day_eps_ttm")

再次读取的时候, 需要指定键的名字

new_eps = pd.read_hdf("./data/test.h5", key="day_eps_ttm")

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
- 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)

结果为：

3.3 to_json

DataFrame.to_json(path_or_buf=None, orient=None, lines=False)
- 将Pandas 对象存储为json格式
- path_or_buf=None：文件地址
- orient:存储的json形式，{‘split’,’records’,’index’,’columns’,’values’}
- lines:一个对象存储为一行

3.4 案例

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 拓展

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
HDF5还是跨平台的，可以轻松迁移到hadoop 上面

5 小结

pandas的CSV、HDF5、JSON文件的读取