如何利用python创建、读取和修改CSV数据文件
目录
- 1 写入CSV文件
- 2 读取CSV文件
- 3 修改CSV文件
- 总结
简单展示如何利用python中的pandas库创建、读取、修改CSV数据文件
1 写入CSV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)
输出如下:
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 8 entries, 0 to 7
Data columns (total 4 columns):
A 8 non-null float64
B 8 non-null float64
C 8 non-null float64
D 8 non-null float64
dtypes: float64(4)
memory usage: 336.0 bytes
-------------------------
A B C D
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0
4 0.0 0.0 0.0 0.0
5 0.0 0.0 0.0 0.0
6 0.0 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0
2 读取CSV文件
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)
输出如下:
<class 'pandas.core.frame.DataFrame'>
A B C D
0 0.0 0.0 0.0 0.0
1 0.0 0.0 0.0 0.0
2 0.0 0.0 0.0 0.0
3 0.0 0.0 0.0 0.0
4 0.0 0.0 0.0 0.0
5 0.0 0.0 0.0 0.0
6 0.0 0.0 0.0 0.0
7 0.0 0.0 0.0 0.0
(8, 4)
<class 'numpy.ndarray'>
[[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]
[0. 0. 0. 0.]]
(8, 4)
3 修改CSV文件
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)
输出如下:
X1 X2 X3 X4 X5 Y
0 1.0 2.0 3.0 4 5 6.0
1 2.0 0.0 0.0 4 5 0.0
2 3.0 0.0 0.0 4 5 0.0
3 4.0 0.0 0.0 4 5 0.0
4 6.0 0.0 0.0 4 5 0.0
5 7.0 0.0 0.0 4 5 0.0
6 8.0 0.0 0.0 4 5 0.0
7 2.0 3.0 4.0 5 6 7.0
参考资料
csv文件的读写与修改还可以通过python的csv库来实现
python中csv文件的创建、读取、修改等操作总结
总结
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