如何利用python创建、读取和修改CSV数据文件

import numpy as np import pandas as pd # -----create an initial numpy array----- # data = np.zeros((8,4)) # print(data.dtype) # print(type(data)) # print(data.shape) # -----from array to dataframe----- # df = pd.DataFrame(data) # print(type(df)) # print(df.shape) # print(df) # -----edit columns and index----- # df.columns = ['A', 'B', 'C', 'D'] df.index = range(data.shape[0]) df.info() # -----save dataframe as csv----- # csv_save_path='./data_.csv' df.to_csv(csv_save_path, sep=',', index=False, header=True) # -----check----- # df = pd.read_csv(csv_save_path) print('-' * 25) print(df) 

import pandas as pd import numpy as np csv_path = './data_.csv' # -----saved as dataframe----- # data = pd.read_csv(csv_path) # ---if index is given in csv file, you can use next line of code to replace the previous one--- # data = pd.read_csv(csv_path, index_col=0) print(type(data)) print(data) print(data.shape) # -----saved as array----- # data_ = np.array(data) # data_ = data.values print(type(data_)) print(data_) print(data_.shape) 

import pandas as pd import numpy as np csv_path = './data_.csv' df = pd.read_csv(csv_path) # -----edit columns and index----- # df.columns = ['X1', 'X2', 'X3', 'Y'] df.index = range(df.shape[0]) # df.index = [i+1 for i in range(df.shape[0])] # -----columns operations----- # Y = df['Y'] df['X4'] = [4 for i in range(df.shape[0])]        # add df['X5'] = [5 for i in range(df.shape[0])] # print(df) df.drop(columns='Y', inplace=True)                # delete # print(df) df['X1'] = [i+1 for i in range(df.shape[0])]      # correct --(1) # df.iloc[:df.shape[0], 0] = [i+1 for i in range(df.shape[0])] # correct --(2) # print(df) df['Y'] = Y_temp # print(df) # -----rows operations----- # df.loc[df.shape[0]] = [i+2 for i in range(6)]     # add # print(df) df.drop(index=4, inplace=True)                    # delete # print(df) df.loc[0] = [i+1 for i in range(df.shape[1])]     # correct # print(df) # -----edit index again after rows operations!!!----- # df.index = range(df.shape[0]) # -----save dataframe as csv----- # csv_save_path='./data_copy.csv' df.to_csv(csv_save_path, sep=',', index=False, header=True) print(df)