python中判断一个dataframe非空 DataFrame有一个属性为empty,直接用DataFrame.empty判断就行。 如果df为空,则 df.empty 返回 True,反之 返回False。 注意empty后面不要加()。 学习tips:查好你自己所用的Pandas对应的版本,在官网上下载Pandas 使用的pdf手册,直接搜索“empty”,就可找到有... 查看原文 pandas中的...
``` # Python script to read and write data to an Excel spreadsheet import pandas as pd def read_excel(file_path): df = pd.read_excel(file_path) return df def write_to_excel(data, file_path): df = pd.DataFrame(data) df.to_excel(file_path, index=False) ``` 说明: 此Python脚本...
# check if there is any element# in the given dataframe or notresult = df.empty# Print the resultprint(result) 输出: 正如我们在输出中看到的,DataFrame.empty属性已返回False指示给定的数据帧不为空。 范例2:采用DataFrame.empty属性,以检查给定的 DataFrame 是否为空。 # importing pandas as pdimportpa...
Python program to check if a Pandas dataframe's index is sorted# Importing pandas package import pandas as pd # Creating two dictionaries d1 = {'One':[i for i in range(10,100,10)]} # Creating DataFrame df = pd.DataFrame(d1) # Display the DataFrame print("Original DataFrame:\n",df...
# check if there is any element # in the given dataframe or not result=df.empty # Print the result print(result) 输出: 正如我们在输出中看到的,DataFrame.empty 属性返回了 False,表示给定的数据帧不为空。示例 #2:使用 DataFrame.empty 属性检查给定的dataframe是否为空。
``` # Python script to read and write data to an Excel spreadsheet import pandas as pd def read_excel(file_path): df = pd.read_excel(file_path) return df def write_to_excel(data, file_path): df = pd.DataFrame(data) df.to_excel(file_path, index=False) ``` 说明: 此Python脚本...
zscore = zscore[~np.isnan(zscore)] 不能用replace方法,replace方法只能用在dataframe上 series.replace(to_replace='None', value=np.nan, inplace=True, regex=False) # 下面两种都是对的,要注意不能串 df_X = df_X.replace([np.inf, -np.inf], np.nan).copy() ...
```# Python script to read and write data to an Excel spreadsheetimport pandas as pddef read_excel(file_path):df = pd.read_excel(file_path)return dfdef write_to_excel(data, file_path):df = pd.DataFrame(data)df.to_excel...
Suppose, we have a column for some student of the same class, the DataFrame will have the following columns: Roll Number Name Age Blood Group Marks We need to check if all the students are of the same age or not or we need to check that does the Age column contains the same values ...
# 读取数据,pd.read_csv默认生成DataFrame对象,需将其转换成Series对象 df=pd.read_csv('AirPassengers.csv',encoding='utf-8',index_col='date')df.index=pd.to_datetime(df.index)# 将字符串索引转换成时间索引 ts=df['x']# 生成pd.Series对象 ...