基于asciichartpy
import asciichartpy data = [1, 2, 3, 4, 5, 4, 3, 2, 1] chart = asciichartpy.plot(data) print(chart)
基于sparklines
import sparklines data = [1, 2, 3, 4, 5, 4, 3, 2, 1] sparkline_str = ''.join(sparklines.sparklines(data)) print(sparkline_str)
基于sparkline-nb将曲线插入dataframe
import io import base64 import numpy as np import pandas as pd import matplotlib.pyplot as plt from IPython.display import display, HTML def sparkline(data, figsize=(4, 0.25), **kwargs): """ Returns an HTML image tag containing a base64 encoded sparkline style plot """ data = list(data) fig, ax = plt.subplots(1, 1, figsize=figsize, **kwargs) ax.plot(data) for k, v in ax.spines.items(): v.set_visible(False) ax.set_xticks([]) ax.set_yticks([]) plt.plot(len(data) - 1, data[len(data) - 1], 'r.') ax.fill_between(range(len(data)), data, [min(data)]*len(data), alpha=0.1) img = io.BytesIO() plt.savefig(img, format='png') img.seek(0) plt.close() # Encode the image in base64 img_base64 = base64.b64encode(img.read()).decode('utf-8') return f'<img src="data:image/png;base64,{img_base64}"/>' if __name__ == "__main__": n = 4 data = [ ('rand', np.random.rand(n)), ('randn', np.random.randn(n)), ('beta', np.random.beta(2, 1, size=n)), ('binomial', np.random.binomial(3.4, 0.22, size=n)), ('exponential', np.random.exponential(size=n)), ('geometric', np.random.geometric(0.5, size=n)), ('laplace', np.random.laplace(size=n)) ] spark = pd.DataFrame(data, columns=['func', 'data']) print(spark) # map the sparkline function over the data column # and store back in the column sparklines spark['sparklines'] = spark.data.map(sparkline) # _repr_html_ escapes HTML so manually handle the rendering HTML(spark.to_html(escape=False))
基于xlsxwriter在Excel里插入曲线
import xlsxwriter wb = xlsxwriter.Workbook('hello.xlsx') ws = wb.add_worksheet() data=[12,23,9,17,31,3,7,21,10,15] ws.write_row('A1', data) ws.set_column('K:K', 40) ws.set_row(0, 30) data=[1,1,-1,-1,-1,1,1,1,-1,-1] ws.write_row('A5', data) ws.set_column('K:K', 40) ws.set_row(4, 30) ws.add_sparkline('K1', {'range':'Sheet1!A1:J1', 'markers':True}) ws.add_sparkline('K5', {'range':'Sheet1!A5:J5', 'type':'win_loss', 'negative_points':True}) wb.close()
基于matplotlib.pyplot先生成png,然后再插入Excel的方法
import os import pandas as pd import matplotlib.pyplot as plt import matplotlib.ticker as mticker from matplotlib import font_manager from openpyxl import load_workbook from openpyxl.drawing.image import Image def insert_pic(excel_path, pic_path, height): if not os.path.exists(excel_path): log.error("failed to insert pic because of missing {}".format(excel_path)) return if not os.path.exists(pic_path): log.error("failed to insert pic because of missing {}".format(pic_path)) return print(excel_path, pic_path) xl = load_workbook(excel_path) xl_sheet = xl[xl.sheetnames[0]] pos = "B" + str(xl_sheet.max_row + height + 5) img = Image(pic_path) xl_sheet.add_image(img, pos) xl.save(excel_path) xl.close()
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标签:ws,xl,Python,data,sparkline,可视化,path,import,数据 From: https://www.cnblogs.com/standby/p/18278640