越界納秒時間戳：日期的 1-01-01 00:00:00

Question

這是我文件的前 10 行。

Year    Revenue
0   Jan-07  1757000
1   Feb-07  2052000
2   Mar-07  2747000
3   Apr-07  2308000
4   May-07  2289000
5   Jun-07  2322000
6   Jul-07  2310000
7   Aug-07  2049000
8   Sep-07  1862000
9   Oct-07  2006000
10  Nov-07  2061000

我開始我的代碼如下：

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
%matplotlib inline
from pandas.plotting import register_matplotlib_converters
from pandas_datareader import data as pdr
from pandas.plotting import autocorrelation_plot
import seaborn as sns

from datetime import datetime
from datetime import timedelta```

I then imported my data set into the file 
```df=pd.read_csv(pathway.csv', sep=',',)

I wanted to see the data types of my file to see what I was working with. 
So I used  ```df.info``` to see what my datafile types were. 

RangeIndex：144 個條目，0 到 143 數據列（共 2 列）：Year 144 非空對象銷售回收材料收入 144 非空 int64 dtypes：int64(1)，object(1) 內存使用：2.3+ K

Then I tried to translate the years into yyyy-mm-dd format by using this code but I error out  with OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1-01-07 00:00:00

df.month = pd.to_datetime(df.month) df.set_index('month', inplace=True)

I expect from my data set to change to 
0   2007-01-01 1757000
1  2007-02-01  2052000
2  2007-03-01  2747000
3  2007-04-01  2308000
4  2007-05-01  2289000
5  2007-06-01  2322000
......

once I complete this i will plot a time series graph, with $ on the y column and x being the date

Answer 1

通過添加缺少的內容來修復您的日期？ 我猜我們可以把這一天定為每月的第一天。

然后將它們轉換為日期時間

df["year"] = "01-" + df["year"]

df["year"] = pd.to_datetime(df["year"], format="%d-%b-%y")

df = df.set_index("year")