读写csv文件
写入到csv文件中：
import numpy as npimport pandas as pd# 通过设置开始时间，并设置间隔了多少月dates = pd.date_range('0101',periods=1000)df = pd.DataFrame(np.random.randn(1000,4),index=dates,columns=['A','B','C','D'])print(df)print("------------将df中的值写入foo.csv中---------------")df.to_csv('foo.csv')print("------------从foo.csv中读取数据---------------")print(pd.read_csv('foo.csv'))
输出结果：
A B C D-01-01 -0.028544 -2.597953 -0.645116 0.403488-01-02 -0.109636 -0.866292 -0.629185 1.072633-01-03 -1.435202 -0.631815 1.208114 -1.647566-01-04 0.368530 -1.073754 -0.712305 -0.513142-01-05 0.813674 -0.081024 -1.153747 0.409363... ... ... ...-09-23 0.783858 -0.330685 0.323741 1.767446-09-24 0.017313 -1.792078 0.686136 0.122491-09-25 0.100742 -1.802797 0.370563 1.297355-09-26 -0.279896 -0.439861 -0.595908 -0.663100-09-27 -0.519504 -1.476432 -0.877358 0.370039[1000 rows x 4 columns]------------将df中的值写入foo.csv中---------------------------从foo.csv中读取数据---------------Unnamed: 0 A B C D0 -01-01 -0.028544 -2.597953 -0.645116 0.4034881 -01-02 -0.109636 -0.866292 -0.629185 1.0726332 -01-03 -1.435202 -0.631815 1.208114 -1.6475663 -01-04 0.368530 -1.073754 -0.712305 -0.5131424 -01-05 0.813674 -0.081024 -1.153747 0.409363..... ... ... ... ...995 -09-23 0.783858 -0.330685 0.323741 1.767446996 -09-24 0.017313 -1.792078 0.686136 0.122491997 -09-25 0.100742 -1.802797 0.370563 1.297355998 -09-26 -0.279896 -0.439861 -0.595908 -0.663100999 -09-27 -0.519504 -1.476432 -0.877358 0.370039[1000 rows x 5 columns]
其中foo.csv文件的内容如下：
读写HDF5
import numpy as npimport pandas as pd# 通过设置开始时间，并设置间隔了多少月dates = pd.date_range('0101',periods=1000)df = pd.DataFrame(np.random.randn(1000,4),index=dates,columns=['A','B','C','D'])print(df)print("------------将df中的值写入foo.h5中---------------")df.to_hdf('foo.h5','df')print("------------从foo.h5中读取数据---------------")print(pd.read_hdf('foo.h5','df'))
输出结果：
A B C D-01-01 -0.204194 -0.753567 -2.08 1.040021-01-02 0.615229 -0.992105 -0.316031 -1.580913-01-03 0.074039 1.371853 1.083735 1.884807-01-04 0.953756 0.682357 -0.163207 1.481403-01-05 2.054147 0.320839 -0.729104 -0.258073... ... ... ...-09-23 -0.058096 -0.230227 -0.423717 -0.551585-09-24 -0.648232 -3.164626 -0.754798 -0.526770-09-25 1.081354 -0.227107 0.103386 1.851068-09-26 -1.245665 -1.518204 0.724717 -0.449273-09-27 0.506393 0.021668 -0.454937 -0.305513[1000 rows x 4 columns]------------将df中的值写入foo.h5中---------------------------从foo.h5中读取数据---------------A B C D-01-01 -0.204194 -0.753567 -2.08 1.040021-01-02 0.615229 -0.992105 -0.316031 -1.580913-01-03 0.074039 1.371853 1.083735 1.884807-01-04 0.953756 0.682357 -0.163207 1.481403-01-05 2.054147 0.320839 -0.729104 -0.258073... ... ... ...-09-23 -0.058096 -0.230227 -0.423717 -0.551585-09-24 -0.648232 -3.164626 -0.754798 -0.526770-09-25 1.081354 -0.227107 0.103386 1.851068-09-26 -1.245665 -1.518204 0.724717 -0.449273-09-27 0.506393 0.021668 -0.454937 -0.305513[1000 rows x 4 columns]
其中foo.h5的内容如下：
读写Excel
import numpy as npimport pandas as pd# 通过设置开始时间，并设置间隔了多少月dates = pd.date_range('0101',periods=1000)df = pd.DataFrame(np.random.randn(1000,4),index=dates,columns=['A','B','C','D'])print(df)print("------------将df中的值写入foo.xlsx中---------------")df.to_excel('foo.xlsx', sheet_name='Sheet1')print("------------从foo.xlsx中读取数据---------------")print(pd.read_excel('foo.xlsx', 'Sheet1', index_col=None, na_values=['NA']))
输出结果：
A B C D-01-01 0.017099 0.527402 0.788463 1.057703-01-02 -0.882500 0.390921 -0.274687 0.870323-01-03 0.404810 -3.034904 -0.527312 -0.076317-01-04 -0.914031 -0.135346 0.027302 -1.019793-01-05 -1.579522 -0.002635 -2.086708 -0.214567... ... ... ...-09-23 -0.421978 1.218736 0.281413 1.574465-09-24 -0.886359 -1.567930 -0.749119 1.831692-09-25 -1.589130 -0.938186 -0.502738 0.599511-09-26 -0.286481 0.644640 0.005656 0.575317-09-27 0.964874 -0.705497 1.027106 0.720334[1000 rows x 4 columns]------------将df中的值写入foo.xlsx中---------------------------从foo.xlsx中读取数据---------------Unnamed: 0 A B C D0 -01-01 0.017099 0.527402 0.788463 1.0577031 -01-02 -0.882500 0.390921 -0.274687 0.8703232 -01-03 0.404810 -3.034904 -0.527312 -0.0763173 -01-04 -0.914031 -0.135346 0.027302 -1.0197934 -01-05 -1.579522 -0.002635 -2.086708 -0.214567.. ... ... ... ... ...995 -09-23 -0.421978 1.218736 0.281413 1.574465996 -09-24 -0.886359 -1.567930 -0.749119 1.831692997 -09-25 -1.589130 -0.938186 -0.502738 0.599511998 -09-26 -0.286481 0.644640 0.005656 0.575317999 -09-27 0.964874 -0.705497 1.027106 0.720334[1000 rows x 5 columns]
其中foo.xlsx的内容如下：
