Python 如何将熊猫文件保存为csv
我有下面的代码如何将df文件保存为csv,如何在另一个程序中获取它,我想提取每个行元素,是否可以在输入相应日期时提取每个元素填充Python 如何将熊猫文件保存为csv,python,pandas,csv,Python,Pandas,Csv,我有下面的代码如何将df文件保存为csv,如何在另一个程序中获取它,我想提取每个行元素,是否可以在输入相应日期时提取每个元素填充 import numpy as np from datetime import datetime,timedelta import pandas as pd # make your data a frame df = pd.DataFrame([[2020, 713000], [ 2019, 703
import numpy as np
from datetime import datetime,timedelta
import pandas as pd
# make your data a frame
df = pd.DataFrame([[2020, 713000],
[ 2019, 703000],
[ 2018, 694000],
[ 2017, 684000],
[ 2016, 674000],
[ 2015, 664000],
[ 2014, 655000],
[ 2013, 645000],
[ 2012, 636000],
[ 2011, 627000]], columns=['DateTime','pop'])
# make DateTime column an datetime object
df['DateTime'] = df['DateTime'].apply(lambda x: datetime(x,1,1))
# create a time range for each day in your period
time_range = np.arange(datetime(2011, 1,1), datetime(2021,1,1), timedelta(days=1))
# make time_range a frame
af = pd.DataFrame(time_range, columns=['DateTime'])
# merge both together (left join on column DateTime) and interpolate the gaps
df = af.merge(df, on='DateTime', how='left').interpolate()
print(df)
我得到输出
DateTime pop
0 2011-01-01 627000.000000
1 2011-01-02 627024.657534
2 2011-01-03 627049.315068
3 2011-01-04 627073.972603
4 2011-01-05 627098.630137
... ... ...
3648 2020-12-27 713000.000000
3649 2020-12-28 713000.000000
3650 2020-12-29 713000.000000
3651 2020-12-30 713000.000000
3652 2020-12-31 713000.000000
查看文档,以便您决定是否要使用任何其他控制参数。df.to\u csv,仅在StackOverflow上搜索pandas csv就返回36080个结果。这是否回答了您的问题?
df.to_csv("my_csvfilename.csv")