【pandas】 之 DataFrame 保存为文件 (df.to

【pandas】 之 DataFrame 保存为文件 (df.to

____tz_zs

DataFrame 数据的保存和读取

<_csv 写入到 csv 文件<_json 写入到 json 文件<_html 写入到 html 文件<_excel 写入到 excel 文件

_csv

将 DataFrame 写入到 csv 文件

._csv.html

_csv(path_or_buf=None, sep=', ', na_rep='', float_format=None, columns=None, header=True, index=True,index_label=None, mode='w', encoding=None, compression=None, quoting=None, quotechar='"',line_terminator='n', chunksize=None, tupleize_cols=None, date_format=None, doublequote=True,escapechar=None, decimal='.')

参数：

• path_or_buf : 文件路径，如果没有指定则将会直接返回字符串的 json
• sep : 输出文件的字段分隔符，默认为 “,”
• na_rep : 用于替换空数据的字符串，默认为''
• float_format : 设置浮点数的格式（几位小数点）
• columns : 要写的列
• header : 是否保存列名，默认为 True ，保存
• index : 是否保存索引，默认为 True ，保存
• index_label : 索引的列标签名

.

# -*- coding:utf-8 -*-"""
@author:    tz_zs
"""import numpy as np
import pandas as pdlist_l = [[11, 12, 13, 14, 15], [21, 22, 23, 24, 25], [31, 32, 33, 34, 35]]
date_range = pd.date_range(start="20180701", periods=3)
df = pd.DataFrame(list_l, index=date_range,columns=['a', 'b', 'c', 'd', 'e'])
print(df)
"""a   b   c   d   e
2018-07-01  11  12  13  14  15
2018-07-02  21  22  23  24  25
2018-07-03  31  32  33  34  35
""&#_csv("tzzs_data.csv")
"""
csv 文件内容：
,a,b,c,d,e
2018-07-01,11,12,13,14,15
2018-07-02,21,22,23,24,25
2018-07-03,31,32,33,34,35
"""
read_csv = pd.read_csv("tzzs_data.csv")
print(read_csv)
"""Unnamed: 0   a   b   c   d   e
0  2018-07-01  11  12  13  14  15
1  2018-07-02  21  22  23  24  25
2  2018-07-03  31  32  33  34  35
""&#_csv("tzzs_data2.csv", index_label="index_label")
"""
csv 文件内容：
index_label,a,b,c,d,e
2018-07-01,11,12,13,14,15
2018-07-02,21,22,23,24,25
2018-07-03,31,32,33,34,35
"""read_csv2 = pd.read_csv("tzzs_data2.csv")
print(read_csv2)
"""index_label   a   b   c   d   e
0  2018-07-01  11  12  13  14  15
1  2018-07-02  21  22  23  24  25
2  2018-07-03  31  32  33  34  35
"""

_json

将 Dataframe 写入到 json 文件

._json.html

_json(path_or_buf=None, orient=None, date_format=None, double_precision=10, force_ascii=True,date_unit='ms', default_handler=None, lines=False, compression=None, index=True)

参数：

• path_or_buf : 文件路径，如果没有指定则将会直接返回字符串的 json。

代码：

df.to_json("tzzs_data.json")read_json = pd.read_json("tzzs_data.json")
print(read_json)
"""a   b   c   d   e
2018-07-01  11  12  13  14  15
2018-07-02  21  22  23  24  25
2018-07-03  31  32  33  34  35
"""

json 文件

{"a": {"1530403200000": 11,"1530489600000": 21,"1530576000000": 31},"b": {"1530403200000": 12,"1530489600000": 22,"1530576000000": 32},"c": {"1530403200000": 13,"1530489600000": 23,"1530576000000": 33},"d": {"1530403200000": 14,"1530489600000": 24,"1530576000000": 34},"e": {"1530403200000": 15,"1530489600000": 25,"1530576000000": 35}
}

_html

将 Dataframe 写入到 html 文件

._html.html

_html(buf=None, columns=None, col_space=None, header=True, index=True, na_rep='NaN', formatters=None,float_format=None, sparsify=None, index_names=True, justify=None, bold_rows=True, classes=None,escape=True, max_rows=None, max_cols=None, show_dimensions=False, notebook=False, decimal='.',border=None, table_id=None)

代码：

df.to_html("tzzs_data.html")read_html = pd.read_html("tzzs_data.html")
print(read_html)
"""
[   Unnamed: 0   a   b   c   d   e
0  2018-07-01  11  12  13  14  15
1  2018-07-02  21  22  23  24  25
2  2018-07-03  31  32  33  34  35]
"""#
print(read_html[0])
"""Unnamed: 0   a   b   c   d   e
0  2018-07-01  11  12  13  14  15
1  2018-07-02  21  22  23  24  25
2  2018-07-03  31  32  33  34  35
"""

HTML文件：

<table border="1" class="dataframe"><thead><tr style="text-align: right;"><th></th><th>a</th><th>b</th><th>c</th><th>d</th><th>e</th></tr></thead><tbody><tr><th>2018-07-01</th><td>11</td><td>12</td><td>13</td><td>14</td><td>15</td></tr><tr><th>2018-07-02</th><td>21</td><td>22</td><td>23</td><td>24</td><td>25</td></tr><tr><th>2018-07-03</th><td>31</td><td>32</td><td>33</td><td>34</td><td>35</td></tr></tbody>
</table>

在浏览器中打开：

.

参考：Pandas Dataframes to_html: Highlighting table rows

# -*- coding: utf-8 -*-
"""
@author: tz_zs
"""
import matplotlib.pyplot as plt
import numpy as np
import pandas as pdindex = ["2018-07-01", "2018-07-02", "2018-07-03", "2018-07-04"]
df = pd.DataFrame(index=index)
df["一"] = [11, 12, 13, 14]
df["二"] = [21, 22, 23, 24]
print(df)
"""一   二
2018-07-01  11  21
2018-07-02  12  22
2018-07-03  13  23
2018-07-04  14  24
"""axes_subplot = df.plot()
# print(type(axes_subplot)) #<class 'matplotlib.axes._subplots.AxesSubplot'>
plt.xlabel("time")
plt.ylabel("num")
plt.legend(loc="best")
id(True)
plt.savefig("test.png")HEADER = '''<html><head><meta charset="UTF-8"></head><body>'''
FOOTER = '''<img src="%s" alt="" width="1200" height="600"></body></html>''' % ("test.png")
with open("test.html", 'w') as f:f.write(HEADER)f._html(classes='df'))f.write(FOOTER)

.

.

_excel

将 DataFrame 写入 excel 文件

_excel

_excel(excel_writer, sheet_name='Sheet1', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, startrow=0, startcol=0, engine=None,merge_cells=True, encoding=None, inf_rep='inf', verbose=True, freeze_panes=None)

.

#!/usr/bin/python2.7
# -*- coding:utf-8 -*-"""
@author:    tz_zs
"""import numpy as np
import pandas as pd
import matplotlib.pyplot as pltlist_l = [[1, 3, 3, 5, 4], [11, 7, 15, 13, 9], [4, 2, 7, 9, 3], [15, 11, 12, 6, 11]]
index = ["2018-07-01", "2018-07-02", "2018-07-03", "2018-07-04"]
df = pd.DataFrame(list_l, index=index, columns=['a', 'b', 'c', 'd', 'e'])
print(df)
"""a   b   c   d   e
2018-07-01   1   3   3   5   4
2018-07-02  11   7  15  13   9
2018-07-03   4   2   7   9   3
2018-07-04  15  11  12   6  11
""&#_excel("test.xls")

.

ImportError: Missing optional dependency 'xlrd'. Install xlrd >= 1.0.0 for Excel support Use pip or conda to install xlrd.