# Import Data df = pd.read_csv("https://github.com/selva86/datasets/raw/master/mpg_ggplot2.csv") # Draw Plot plt.figure(figsize=(13,10), dpi=80) sns.distplot(df.loc[df['class']=='compact',"cty"], color="dodgerblue", label="Compact", hist_kws={'alpha':.7}, kde_kws={'li...
df[visitor_type_column] = df[visitor_type_column].map(weather_mapping) # 绘制饼状图,展示游客类型分布情况 plt.figure(figsize=(10,7)) plt.pie(df[visitor_type_column].value_counts(), labels=df[visitor_type_column].unique(), autopct='%1.1f%%') plt.title('Visitor Type Distribution') plt...
max_sigma=30, num_sigma=10, threshold=.1) log_blobs[:, 2] = sqrt(2) * log_blobs[:, 2] # Compute radius in the 3rd column dog_blobs = blob_dog(im_gray, max_sigma=30, threshold=0.1
#Create a function to build a regression model with parameterized degree of independent coefficientsdefcreate_model(x_train,degree): degree+=1X_train = np.column_stack([np.power(x_train,i)foriinrange(0,degree)]) model = np.dot(np.dot(np.linalg.inv(np.dot(X_train.transpose(),X_train...
iloc[0] #loc属性 (label based locating) 用于根据索引获取值。根据索引腾讯获取对应股价54.74 stockS.loc['腾讯'] 向量相加时,只会在索引对上的部分相加。 向量相加(按索引),删除缺失值,将缺失值填充 三、二维数据分析 3.1 、NumPy (Array) #定义二维数组 import numpy as np; # 导入包 a = np.array...
groupby(column_name).mean() # 按列名分组并计算均值 df[column_name].apply(function) # 对某一列应用自定义函数 数据可视化 import matplotlib.pyplot as plt # 绘制柱状图 df[column_name].plot(kind="bar") # 绘制散点图 df.plot(x="column_name1", y="column_name2", kind="scatter"...
index_label : str or sequence, or False, default None Column label for index column(s) if desired. If None is given, and `header` and `index` are True, then the index names are used. A sequence should be given if the object uses MultiIndex. If False do not print fields for index...
db_column:字段的名称,如果未指定,则使用属性的名称 db_index:若值为True,则在表中会为此字段创建索引 default:默认值 primary_key:若为True,则该字段会成为模型的主键字段 unique:如果为True,该字段在表中必须有唯一的值 verbose_name:字段的一种说明,在form中不会显示,和label是这个Field在form中会显示的文本...
Column names in the DataFrame to be encoded. If columns is None then all the columns with object or category dtype will be converted. sparse: bool, default False Whether the dummy-encoded columns should be backed by aSparseArray(True) or a regular NumPy array (False). ...
This can be helpful for referring to the image in the future. If you leave the field blank, the image will have only a random unique identifier. Build options Set supporteddocker buildoptions. For example, you can specify metadata for the built image with the--labeloption. ...