DA
来自Jack's Lab
(版本间的差异)
(→bar) |
(→探索数据分布) |
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第25行: | 第25行: | ||
* [https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.kde.html Pandas KDE] | * [https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.kde.html Pandas KDE] | ||
+ | * [https://matplotlib.org/tutorials/introductory/lifecycle.html#sphx-glr-tutorials-introductory-lifecycle-py X 轴 label 格式] | ||
=== bar === | === bar === |
2020年2月16日 (日) 19:58的版本
目录 |
1 Overview
2 描述性统计
3 探索数据分布
3.1 bar
import pandas as pd import matplotlib.pyplot as plt import matplotlib.dates as mdate hb = pd.read_csv("../DA/data/ncp-hb-new.csv", index_col='Date', parse_dates=True, skipinitialspace=True) cn = pd.read_csv("../DA/data/ncp-cn-new.csv", index_col='Date', parse_dates=True, skipinitialspace=True) xhb = cn-hb plt.gca().xaxis.set_major_formatter(mdate.DateFormatter('%m-%d')) plt.bar(hb.index, hb['Confirmed'].values) plt.bar(xhb.index, xhb['Confirmed'].values) plt.show()
4 时序数据分析
5 Reference
- Numpy API reference
- Pandas API reference
- matplotlib Gallery
- Change the Colors Changes to the default style
- matplotlib.pyplot.plot()
- matplotlib.pyplot.figure()
- Time Series Analysis Example
- Introduction to Data Science
- Data Visualization tutorial
- FlowingData Tutorials