- 一、PandasGUI简介
- 二、下载安装
- 三、PandasGUI官网实例
- 3.1 官网实例导入
- 3.2 静态统计
- 3.3 条件过滤
- 3.4 图表可视化
- 3.5 数据reshape
- 四、Covid-19数据展示
- 4.1 数据集介绍
- 4.2 数据提取与准备
- 4.3 可视化分析界面
Pandasgui为pandas创建了一个GUI界面，我们可以在其中使用pandas的功能分析数据和使用不同的功能，以便可视化和分析数据，并执行探索性数据分析。
官网地址：https://github.com/adamerose/PandasGUI
安装方法
使用说明
功能简介
其他说明
依赖有点多，建议利用国内源下载
pip install -i https://pypi.douban.com/simple pandasgui
(env_study) PS E:python_studyenv_study> pip install -i https://pypi.douban.com/simple pandasgui
Looking in indexes: https://pypi.douban.com/simple
Collecting pandasgui
Downloading https://pypi.doubanio.com/packages/70/60/dfbe9817d621bb6868427283273e17c1209d0c5b763106a75acccd44ebda/pandasgui-0.2.13.tar.gz (215 kB)
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Collecting matplotlib-inline
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Downloading https://pypi.doubanio.com/packages/c6/37/ec72228971dbaf191243b8ee383c6a3834b5cde23daab066dfbfbbd5438b/prompt_toolkit-3.0.20-py3-none-any.whl (370 kB)
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Collecting backcall
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Collecting decorator
Downloading https://pypi.doubanio.com/packages/3d/cc/d7b758e54779f7e465179427de7e78c601d3330d6c411ea7ba9ae2f38102/decorator-5.1.0-py3-none-any.whl (9.1 kB)
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Collecting PyQtWebEngine-Qt5>=5.15
Downloading https://pypi.doubanio.com/packages/e0/db/0f29bd882aee8b5754f3e1ab104d2d09cdd9138a889558b43badcd81ce11/PyQtWebEngine_Qt5-5.15.2-py3-none-win_amd64.whl (60.0 MB)
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Requirement already satisfied: pillow in e:python_studyenv_studylibsite-packages (from wordcloud->pandasgui) (8.3.1)
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Building wheels for collected packages: pandasgui, qtstylish, wordcloud
Building wheel for pandasgui (setup.py) ... done
Created wheel for pandasgui: filename=pandasgui-0.2.13-py3-none-any.whl size=233725 sha256=64f5d850ba6cac8d2d510ee1ba58441974e48ad96b7db92dce1b679718dff0ad
Stored in directory: c:usersadministratorappdatalocalpipcachewheels42e329f3c748ebd0327ddc1c0f9a54f7747ac48f10125435dd8334ce
Building wheel for qtstylish (setup.py) ... done
Created wheel for qtstylish: filename=qtstylish-0.1.5-py3-none-any.whl size=1029285 sha256=3f6dca6153389fe26f6cf8e59d1adfbae6394a03447282a3e7bd2a2ad5dc8a14
Stored in directory: c:usersadministratorappdatalocalpipcachewheelsac60212adfa6e056d94dd686ab9165e3d61c6c589ef00bf9ad252952
Building wheel for wordcloud (setup.py) ... done
Created wheel for wordcloud: filename=wordcloud-1.8.1-cp39-cp39-win_amd64.whl size=154800 sha256=4d12b8f009520f8864b4ead3619d62965dbf34a5f789c65f65416ee55626c01f
Stored in directory: c:usersadministratorappdatalocalpipcachewheelsbc9fd57c5937d1f37c9a6607fdd1709263669b801c1555226371adc0
Successfully built pandasgui qtstylish wordcloud
Installing collected packages: traitlets, parso, PyQtWebEngine-Qt5, pygments, prompt-toolkit, pickleshare, matplotlib-inline, jedi, decorator, backcall, wordcloud, typing-exte
nsions, qtstylish, PyQtWebEngine, pyarrow, IPython, astor, appdirs, pandasgui
Successfully installed IPython-7.28.0 PyQtWebEngine-5.15.4 PyQtWebEngine-Qt5-5.15.2 appdirs-1.4.4 astor-0.8.1 backcall-0.2.0 decorator-5.1.0 jedi-0.18.0 matplotlib-inline-0.1.
3 pandasgui-0.2.13 parso-0.8.2 pickleshare-0.7.5 prompt-toolkit-3.0.20 pyarrow-5.0.0 pygments-2.10.0 qtstylish-0.1.5 traitlets-5.1.0 typing-extensions-3.10.0.2 wordcloud-1.8.1
(env_study) PS E:python_studyenv_study>
三、PandasGUI官网实例
3.1 官网实例导入
3.2 静态统计
3.3 条件过滤
3.4 图表可视化
3.5 数据reshape
四、Covid-19数据展示
4.1 数据集介绍
2019-2020年世界Covid-19数据，近23万行，42列
import pandas as pd
from pandasgui import show
import os
import datetime
# 分块
chunks = pd.read_csv("../data/covid-19.csv", chunksize=10000) # 生成一个文本读取器，并没有真正去读文件
total = 0
file = "../data/result_分块分列.csv"
if os.path.exists(file):
os.remove(file)
for i, df in enumerate(chunks):
# 处理空值：删除全为空值的列
df.dropna(how="all", inplace=True, axis=1)
result = []
# 拿到有用列
df = df[['date', 'country', 'countryCode', '/confirm/ied']]
for a, b, c, d in df.values:
if not isinstance(a, str): # 如果data不是str类型，就抛弃本行数据
continue
# 提取指定年月的数据
if a.split("-")[0] == '2020' and 1 <= int(a.split("-")[1]) <= 8:
result.append((*a.split("-"), b, d)) # 结果为 [()]，生成df时，元组列表常用
total += 1
df = pd.Dataframe(result, columns=["年", "月", "日", "国家", "数量"])
df.to_csv(file, index=False, mode='a', header=not os.path.exists(file), encoding="utf-8")
df = pd.read_csv(file, converters={'年': str, '月': str, '日': str})
show(df)
4.3 可视化分析界面
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数据框页面
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静态数据统计
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数据可视化
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可视化代码导出
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图表保存为png图片
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导出的图片
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查看关键参数
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折线图
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条形图
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箱型图
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小提琴图
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3D散点图
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热力图
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等高线图
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饼图
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散点图矩阵
