Question

我有一个包含财务数据（日期，开盘价，收盘价，低价，高价）的数据框。

我想用一栏（例如打开）来绘制日期。当我将“日期”列转换为日期时，图形无法正确显示。为什么会发生这种情况？

import pandas as pd
import matplotlib.pyplot as plt

def plot_one_data(df, column, title= "No Title", color = "black"):

    df.plot(x="Date", y=column, title=title)
    #show plot
    filename= title+ ".png"
    plt.savefig(filename)


#Load in the csv files
df = pd.read_csv('data/df.csv')
print(df.head())
plot_one_data(df, "Open", "Before Converting to Date - good but no dates on x axis")


df['Date'] = pd.to_datetime(df["Date"])
print(df.head())
plot_one_data(df, "Open", "After Converting to Date - bad!")

文本输出：

       Date         Open     ...        Adj Close      Volume
0  14-08-06  1266.670044     ...      1268.209961  2118020000
1  15-08-06  1268.189941     ...      1285.579956  2334100000
2  16-08-06  1285.270020     ...      1295.430054  2554570000
3  17-08-06  1295.369995     ...      1297.479980  2458340000
4  18-08-06  1297.479980     ...      1302.300049  2033910000

[5 rows x 7 columns]
        Date         Open     ...        Adj Close      Volume
0 2006-08-14  1266.670044     ...      1268.209961  2118020000
1 2006-08-15  1268.189941     ...      1285.579956  2334100000
2 2006-08-16  1285.270020     ...      1295.430054  2554570000
3 2006-08-17  1295.369995     ...      1297.479980  2458340000
4 2006-08-18  1297.479980     ...      1302.300049  2033910000

Answer 1

解决方案-添加格式

更新的行

df['Date'] = pd.to_datetime(df["Date"], format='%d-%m-%y')

我发现查看前30个条目（更改为日期时间之前和之后）很有帮助。它一直有效到2006年8月底，然后跳至1月9日！

原始数据中的前30个条目

        Date         Open     ...        Adj Close      Volume
0   14-08-06  1266.670044     ...      1268.209961  2118020000
1   15-08-06  1268.189941     ...      1285.579956  2334100000
2   16-08-06  1285.270020     ...      1295.430054  2554570000
3   17-08-06  1295.369995     ...      1297.479980  2458340000
4   18-08-06  1297.479980     ...      1302.300049  2033910000
5   21-08-06  1302.300049     ...      1297.520020  1759240000
6   22-08-06  1297.520020     ...      1298.819946  1908740000
7   23-08-06  1298.729980     ...      1292.989990  1893670000
8   24-08-06  1292.969971     ...      1296.060059  1930320000
9   25-08-06  1295.920044     ...      1295.089966  1667580000
10  28-08-06  1295.089966     ...      1301.780029  1834920000
11  29-08-06  1301.569946     ...      1304.280029  2093720000
12  30-08-06  1303.699951     ...      1305.369995  2060690000
13  31-08-06  1304.250000     ...      1303.819946  1974540000 #Smooth change from August to September
14  01-09-06  1303.800049     ...      1311.010010  1800520000
15  05-09-06  1310.939941     ...      1313.250000  2114480000
16  06-09-06  1313.040039     ...      1300.260010  2329870000
17  07-09-06  1300.209961     ...      1294.020020  2325850000
18  08-09-06  1294.020020     ...      1298.920044  2132890000
19  11-09-06  1298.859985     ...      1299.540039  2506430000
20  12-09-06  1299.530029     ...      1313.000000  2791580000
21  13-09-06  1312.739990     ...      1318.069946  2597220000
22  14-09-06  1318.000000     ...      1316.280029  2351220000
23  15-09-06  1316.280029     ...      1319.660034  3198030000
24  18-09-06  1319.849976     ...      1321.180054  2325080000
25  19-09-06  1321.170044     ...      1317.640015  2390850000
26  20-09-06  1318.280029     ...      1325.180054  2543070000
27  21-09-06  1324.890015     ...      1318.030029  2627440000
28  22-09-06  1318.030029     ...      1314.780029  2162880000
29  25-09-06  1314.780029     ...      1326.369995  2710240000

更改为日期时间后的前30个条目

[30 rows x 7 columns]
         Date         Open     ...        Adj Close      Volume
0  2006-08-14  1266.670044     ...      1268.209961  2118020000
1  2006-08-15  1268.189941     ...      1285.579956  2334100000
2  2006-08-16  1285.270020     ...      1295.430054  2554570000
3  2006-08-17  1295.369995     ...      1297.479980  2458340000
4  2006-08-18  1297.479980     ...      1302.300049  2033910000
5  2006-08-21  1302.300049     ...      1297.520020  1759240000
6  2006-08-22  1297.520020     ...      1298.819946  1908740000
7  2006-08-23  1298.729980     ...      1292.989990  1893670000
8  2006-08-24  1292.969971     ...      1296.060059  1930320000
9  2006-08-25  1295.920044     ...      1295.089966  1667580000
10 2006-08-28  1295.089966     ...      1301.780029  1834920000
11 2006-08-29  1301.569946     ...      1304.280029  2093720000
12 2006-08-30  1303.699951     ...      1305.369995  2060690000
13 2006-08-31  1304.250000     ...      1303.819946  1974540000 #Fine until here
14 2006-01-09  1303.800049     ...      1311.010010  1800520000 #Problem here
15 2006-05-09  1310.939941     ...      1313.250000  2114480000
16 2006-06-09  1313.040039     ...      1300.260010  2329870000
17 2006-07-09  1300.209961     ...      1294.020020  2325850000
18 2006-08-09  1294.020020     ...      1298.920044  2132890000
19 2006-11-09  1298.859985     ...      1299.540039  2506430000
20 2006-12-09  1299.530029     ...      1313.000000  2791580000
21 2006-09-13  1312.739990     ...      1318.069946  2597220000
22 2006-09-14  1318.000000     ...      1316.280029  2351220000
23 2006-09-15  1316.280029     ...      1319.660034  3198030000
24 2006-09-18  1319.849976     ...      1321.180054  2325080000
25 2006-09-19  1321.170044     ...      1317.640015  2390850000
26 2006-09-20  1318.280029     ...      1325.180054  2543070000
27 2006-09-21  1324.890015     ...      1318.030029  2627440000
28 2006-09-22  1318.030029     ...      1314.780029  2162880000
29 2006-09-25  1314.780029     ...      1326.369995  2710240000

这是固定图像：

为什么将“日期”列更改为日期时间破坏图？

1 个答案: