一.文件读取与存储

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'open', 'close'指标
data = pd.read_csv("./data/stock_day.csv", usecols=['open', 'close'])open    high    close
2018-02-27    23.53    25.88    24.16
2018-02-26    22.80    23.78    23.53
2018-02-23    22.88    23.37    22.82
2018-02-22    22.25    22.76    22.28
2018-02-14    21.49    21.99    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 :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("./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.to_hdf(path_or_buf, key, **kwargs)

2.2 案例

读取文件

day_eps_ttm = pd.read_hdf("./data/stock_data/day/day_eps_ttm.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_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

二.案例实现

1 csv

import pandas as pd

In [4]:

data = pd.read_csv("./data/stock_day.csv", usecols=["open", "high"])

In [5]:

data.head()

Out[5]:

	open	high
2018-02-27	23.53	25.88
2018-02-26	22.80	23.78
2018-02-23	22.88	23.37
2018-02-22	22.25	22.76
2018-02-14	21.49	21.99

In [8]:

data[:10].to_csv("./data/test_py38.csv", columns=["open"], index=False)

2 hdf5

In [9]:

data= pd.read_hdf("./data/stock_data/day/day_close.h5")

In [11]:

data.head()

Out[11]:

	000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	…	001965.SZ	603283.SH	002920.SZ	002921.SZ	300684.SZ	002922.SZ	300735.SZ	603329.SH	603655.SH	603080.SH
0	16.30	17.71	4.58	2.88	14.60	2.62	4.96	4.66	5.37	6.02	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	17.02	19.20	4.65	3.02	15.97	2.65	4.95	4.70	5.37	6.27	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	17.02	17.28	4.56	3.06	14.37	2.63	4.82	4.47	5.37	5.96	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	16.18	16.97	4.49	2.95	13.10	2.73	4.89	4.33	5.37	5.77	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	16.95	17.19	4.55	2.99	13.18	2.77	4.97	4.42	5.37	5.92	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

5 rows × 3562 columns

In [13]:

test_data = data.to_hdf("./data/test_py38.h5", key="close")

In [15]:

pd.read_hdf("./data/test_py38.h5", key="close").head()

Out[15]:

	000001.SZ	000002.SZ	000004.SZ	000005.SZ	000006.SZ	000007.SZ	000008.SZ	000009.SZ	000010.SZ	000011.SZ	…	001965.SZ	603283.SH	002920.SZ	002921.SZ	300684.SZ	002922.SZ	300735.SZ	603329.SH	603655.SH	603080.SH
0	16.30	17.71	4.58	2.88	14.60	2.62	4.96	4.66	5.37	6.02	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1	17.02	19.20	4.65	3.02	15.97	2.65	4.95	4.70	5.37	6.27	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
2	17.02	17.28	4.56	3.06	14.37	2.63	4.82	4.47	5.37	5.96	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
3	16.18	16.97	4.49	2.95	13.10	2.73	4.89	4.33	5.37	5.77	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN
4	16.95	17.19	4.55	2.99	13.18	2.77	4.97	4.42	5.37	5.92	…	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN

5 rows × 3562 columns

3 json

In [17]:

data = pd.read_json("./data/Sarcasm_Headlines_Dataset.json", orient="records", lines=True)

In [19]:

data.head()

Out[19]:

	article_link	headline	is_sarcastic
0	https://www.huffingtonpost.com/entry/versace-b…	former versace store clerk sues over secret 'b…	0
1	https://www.huffingtonpost.com/entry/roseanne-…	the ‘roseanne’ revival catches up to our thorn…	0
2	https://local.theonion.com/mom-starting-to-fea…	mom starting to fear son’s web series closest …	1
3	https://politics.theonion.com/boehner-just-wan…	boehner just wants wife to listen, not come up…	1
4	https://www.huffingtonpost.com/entry/jk-rowlin…	j.k. rowling wishes snape happy birthday in th…	0

In [21]:

data.to_json("./data/test_py38.json", orient="records", lines=True)

机器学习3：——Pandas——3：文件读取和存储相关推荐

Pandas：文件读取、存储【读取：read_**()、写入：to_**()】【文件类型：csv、excel、json、HDF5】
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 CS ...
Pandas之文件读取与存储
文件读取与存储 1 CSV 1.1 read_csv 1.2 to_csv 1.3案例 2 HDF5 2.1 read_hdf与to_hdf 2.2案例 3 JSON 3.1 read_json 3. ...
pandas文件读取与存储
pandas文件读取与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H ...
学习笔记Spark（四）—— Spark编程基础（创建RDD、RDD算子、文件读取与存储）
文章目录一.创建RDD 1.1.启动Spark shell 1.2.创建RDD 1.2.1.从集合中创建RDD 1.2.2.从外部存储中创建RDD 任务1: 二.RDD算子 2.1.map与flat ...
python:文件读取和存储
文章目录一.文件的打开.读取.加载 1.python内置函数:open()打开.f.read()读取 2.pandas库 3.numpy库二.文件的写入.存储 1.python内置函数:f.wri ...
3-7 pandas数据的读取与存储
数据分析工具pandas 7. 数据的读取与存储 7.1 读操作 7.2 写操作 7.3 JSON格式 7.4 分块读取大文件 Pandas是一个强大的分析结构化数据的工具集,基于NumPy构建,提供 ...
pandas parquet文件读取pyarrow、feather文件保存与读取；requests 或wget下载图片文件
**pandas读取文件填写绝对路径,相对路径可能出错读不了安装 fastparquet库,需要安装python-snappy ,一直安装错误,所以使用了pyarrow pip install py ...
在Python中使用pandas进行文件读取和写入方法详解
Pandas 是 Python 的一个功能强大且灵活的三方包,可处理标记和时间序列数据.还提供统计方法.启用绘图等功能.Pandas 的一项重要功能是能够编写和读取 Excel.CSV 和许多其他类型 ...
php大文件读取和存储,php存储大文件思路
这个似乎是没办法. 看这段: 在图片上传部分,其实能玩的花样很少,但是编写代码所消耗的时间最多.现在我们再假设一种情景,如果我们的图片服务器前端采用Nginx,上传功能用PHP实现,需要写的代码很少 ...

机器学习3：——Pandas——3：文件读取和存储