def scatterplot(x_data, y_data, x_label="", y_label="", title="", color = "r", yscale_log=False): # Create the plot object _, ax = plt.subplots() # Plot the data, set the size (s), color and transparency (alpha) # of the points ax.scatter(x_data, y_data, s = 10...
sns.scatterplot(x="total_bill", y="tip", data=tips)plt.title('total bill vs tip')plt.show() 3. 探索性数据分析 (exploratory data analysis, eda) eda 是在没有明确假设的情况下使用图表和其他统计方法来了解数据的过程。 使用pandas 和matplotlib...
fig = px.scatter(data_frame=data, x='feature_1', y='target', color='category', title='Interactive Scatter Plot') fig.show() 1. 2. 3. 4. 5. 5. 构建交互式仪表板:使用Dash Dash是由Plotly开发的一个框架,可以轻松构建Web应用和交互式仪表板。
df['Diagnosis'].value_counts().plot(kind='bar',color=['green','red'])plt.title('Diagnosis Distribution')plt.xlabel('Diagnosis')plt.ylabel('Patient Count')plt.show() 解释:该图显示了每个诊断类别(如“Healthy”与“Hypertension”)的人数分布,方便医生快速了解整体健康状况。
ax = data.plot( column="childrenNum", scheme="QUANTILES",# 设置分层设色标准 edgecolor='lightgrey', k=7,# 分级数量 cmap="Blues", legend=True, # 通过fmt设置位数 legend_kwds={"loc":"center left","bbox_to_anchor": (1,0.5),"fmt":"{:.2f}"} ...
Step 2 — Creating Data Points to Plot In our Python script, let’s create some data to work with. We are working in 2D, so we will need X and Y coordinates for each of our data points. To best understand how matplotlib works, we’ll associate our data with a possible real-life ...
# Some boilerplate to initialise things sns.set() plt.figure() # This is where the actual plot gets made ax= sns.barplot(data=df, x="year", y="seats", hue="party", palette=['blue','red','yellow','grey'], saturation=0.6) ...
data data.iloc[0] 1. 2. 3. 使用merge函数将ratings,users和movies进行合并,保留了三个DataFrame中所有的数据,并将他们之间重复的数据和行进行合并。合并生成名为data的新DataFrame,并输出整个数据以及读取第一行数据。 mean_ratings = data.pivot_table("rating", index="title", ...
df.groupby('区域')['销售额'].sum().sort_values().plot.barh() # 条形图 使用plot.pie函数可...
lake_color='aqua') map.drawcoastlines() plt.show()由于basemap无所不能的绘图能力，你还可以画...