Joolin20.0JJNaNJay46.0dtype:float64 对于许多应用而言,Series有一个重要的功能:在算术运算中,它可以自动对齐不同索引的数据。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 sdata={'Joolin':20,'Jay':46}states=['Joolin','DT','Jay']obj1=pd.Series(sdata)
arrays = [[1, 1, 2, 2], ['red', 'blue', 'red', 'blue']] pd.MultiIndex.from_arrays(arrays, names=('number', 'color')) # 结果 MultiIndex(levels=[[1, 2], ['blue', 'red']], codes=[[0, 0, 1, 1], [1, 0, 1, 0]], names=['number', 'color']) 2、Panel (1)...
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"...
nunique 函数是 pandas 中用于计算 DataFrame 或 Series 中唯一值的数量的函数。nunique 是 "number of unique" 的缩写，它返回一个标量值，表示唯一值的数量。以下是 nunique 函数的详细解释和用法：DataFrame/Series.nunique(axis=, dropna=True)主要参数：axis：默认为 0，用于指定计算唯一值数量的轴，0 表示...
Series s.loc[indexer] DataFrame df.loc[row_indexer,column_indexer] 基础知识 如在上一节介绍数据结构时提到的,使用[](即__getitem__,对于熟悉在 Python 中实现类行为的人)进行索引的主要功能是选择较低维度的切片。以下表格显示了使用[]索引pandas 对象时的返回类型值: 对象类型 选择 返回值类型 Series seri...
concat([df['Name'],df['Age'],df['Gender']]).unique() # Display result print("Unique values:\n",result) OutputThe output of the above program is:Python Pandas Programs »Find the column name which has the maximum value for each row How to modify a subset of rows in a pandas ...
Pandas provides several methods for handling unique values, including −nunique(): Counts the number of distinct values in each column or row. value_counts(): Returns the frequency of each unique value in an object. unique()Retrieves unique values based on a hash table....
infer_objects() Change the dtype of the columns in the DataFrame info() Prints information about the DataFrame insert() Insert a column in the DataFrame interpolate() Replaces not-a-number values with the interpolated method isin() Returns True if each elements in the DataFrame is in the spe...
当索引没有对应的值时,可能出现缺失数据显示NaN(not a number)的情况。注意:np.NaN != np.NaN;可以使用pd.isnull(),pd.notnull(),或自带isnull(),notnull()函数检测缺失数据。 1#造一含有NaN值的Series数据2s5 = Series(data=range(4),index=list('abcd'))#NaN是float3s5['c'] = np.nan#将索引...
Suppose we are given the dataframe containing two columns each of which has repeating values, we need to figure out how to count by the number of rows for unique pair of columns. DataFrame stack multiple column values into single column ...