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Python 代码将 DataFrame 表（面板数据？）转换为时间序列？

[英]Python code to convert DataFrame table (Panel data?) to time-series?

 原文  2022-01-15 21:04:42  9   1    python/ pandas/ dataframe/ time-series

问题描述

I am downloading an Eurostat dataset in Python using the eurostat package and the Dataframe format is tricky to work with.我正在使用 Eurostat package 下载 Python 中的 Eurostat 数据集，而 Dataframe 格式很难使用。 I have been trying to turn the panel data into time-series, but I have not been successful.我一直在尝试将面板数据转换为时间序列，但没有成功。

I have filtered and cleaned the data a little bit, but I've failed to turn the table into time-series (I am fairly new to Python).我已经对数据进行了一些过滤和清理，但是我未能将表格转换为时间序列（我对 Python 还很陌生）。 Below my code:在我的代码下面：

#pip install eurostat
import pandas as pd
import eurostat

# Commercial flights by reporting country – monthly data (source: Eurocontrol)
df_eurostat = eurostat.get_data_df('avia_tf_cm')
df_eurostat = df_eurostat.rename(columns={'geo\\time':'Region'})

# To exclude: 'EU27_2020', 'EU28'
# df_eurostat = df_eurostat.drop(columns='unit').T
country_list = ['AL', 'AT', 'BE', 'BG', 'CH', 'CY', 'CZ', 'DE', 'DK', 'EE', 'EL',
                'ES', 'FI', 'FR', 'HR', 'HU', 'IE', 'IS', 'IT', 'LT', 'LU', 'LV',
                'ME', 'MK', 'MT', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 
                'SK', 'TR', 'UK']

df_eurostat = df_eurostat[df_eurostat['Region'].isin(country_list)]
df_eurostat = df_eurostat.loc[(df_eurostat['unit']=='NR')]

Before:前： 在此处输入图像描述

After - what I want to achieve:之后 - 我想要实现的目标： 在此处输入图像描述

Would highly appreciate it if anyone could help.如果有人可以提供帮助，将不胜感激。 Thank you in advance!先感谢您！

1 个解决方案

解决方案1
 0 已采纳  2022-01-15 21:30:48

One more step:更进一步：

to_date = lambda x: pd.to_datetime(x['Date'], format='%YM%m')

df_eurostat = df_eurostat.drop(columns='unit').set_index('Region').T \
                         .rename_axis(index='Date', columns=None) \
                         .reset_index().assign(Date=to_date)

Output: Output：

>>> df_eurostat
         Date      AL       AT       BE       BG       CH      CY       CZ        DE       DK  ...       NO       PL       PT       RO      RS       SE      SI      SK        TR        UK
0  2021-12-01  2265.0  15224.0  20055.0   4188.0  24102.0  3851.0   6690.0   94592.0  17277.0  ...  32284.0  23299.0  23977.0  10653.0  3804.0  19148.0  1038.0  1224.0   55338.0   96922.0
1  2021-11-01  1953.0  15513.0  20445.0   3694.0  21180.0  4452.0   6549.0   96853.0  17630.0  ...  33727.0  22105.0  23334.0   9294.0  3578.0  19088.0   993.0  1040.0   57975.0   90265.0
2  2021-10-01  2358.0  18314.0  21520.0   4945.0  26289.0  7118.0   7019.0  115037.0  18805.0  ...  33051.0  23325.0  27620.0  11708.0  4017.0  19070.0  1137.0  1178.0   81820.0  103358.0
3  2021-09-01  2998.0  18856.0  21834.0   6853.0  24979.0  6488.0   7785.0  107754.0  17609.0  ...  31901.0  25523.0  26989.0  13370.0  4691.0  18503.0  1155.0  1453.0   81744.0   98183.0
4  2021-08-01  3705.0  19579.0  22261.0   8807.0  26451.0  6873.0   7815.0  106657.0  16538.0  ...  28870.0  26381.0  29506.0  14416.0  5761.0  17061.0  1268.0  1695.0   90404.0   92697.0
5  2021-07-01  2973.0  17697.0  21617.0   7663.0  24531.0  6418.0   7291.0   99334.0  15357.0  ...  26152.0  24355.0  26176.0  13446.0  5831.0  15591.0  1210.0  1608.0   87664.0   72389.0
6  2021-06-01  2173.0  11225.0  15313.0   4441.0  15021.0  4328.0   5151.0   68482.0   8958.0  ...  21798.0  17129.0  19879.0  10222.0  3955.0  11832.0   788.0   992.0   58319.0   50648.0
7  2021-05-01  1452.0   7783.0  11247.0   2796.0  11619.0  3016.0   3051.0   51870.0   5993.0  ...  19007.0   8933.0  13758.0   6936.0  2736.0   8661.0   592.0   436.0   36572.0   35027.0
8  2021-04-01  1039.0   6632.0   9537.0   2457.0  10199.0  1872.0   2310.0   45712.0   4994.0  ...  18183.0   7256.0  10086.0   5720.0  2203.0   7683.0   455.0   280.0   39540.0   27739.0
9  2021-03-01   935.0   5327.0   8454.0   2071.0   8431.0  1334.0   2174.0   39463.0   4615.0  ...  19120.0   6120.0   6216.0   4212.0  1829.0   7502.0   479.0   377.0   38896.0   25305.0
10 2021-02-01   751.0   3976.0   7836.0   1756.0   7116.0   992.0   1889.0   30330.0   3522.0  ...  16159.0   4553.0   5134.0   3543.0  1527.0   6274.0   391.0   418.0   30167.0   20496.0
11 2021-01-01   881.0   4801.0   9481.0   2229.0   9262.0  1064.0   2208.0   36932.0   4937.0  ...  18953.0   6943.0   9227.0   4555.0  1741.0   7203.0   402.0   444.0   32167.0   28100.0
12 2020-12-01   880.0   5271.0  10360.0   2577.0   9804.0  1316.0   2572.0   39709.0   6030.0  ...  18913.0   7898.0  10387.0   4463.0  1887.0   8003.0   416.0   521.0   29614.0   38484.0
13 2020-11-01   872.0   5409.0   9787.0   2265.0   7667.0  1528.0   2248.0   40854.0   6328.0  ...  21194.0   8035.0   9738.0   3661.0  2130.0   8903.0   404.0   362.0   36441.0   34516.0
14 2020-10-01  1227.0   9237.0  11507.0   3392.0  12132.0  3185.0   3271.0   64376.0   9356.0  ...  24317.0  13245.0  15886.0   6179.0  2817.0  11103.0   577.0   653.0   49092.0   61735.0
15 2020-09-01  1513.0  11990.0  12241.0   4429.0  14364.0  3464.0   4749.0   69292.0  10604.0  ...  24939.0  15927.0  17980.0   7112.0  2845.0  10819.0   664.0   901.0   51449.0   72451.0
16 2020-08-01  2087.0  13469.0  14772.0   5396.0  18023.0  3770.0   5157.0   73205.0  10657.0  ...  24069.0  18681.0  20945.0   8059.0  2898.0   9963.0   796.0  1114.0   51758.0   79123.0
17 2020-07-01  1754.0  10377.0  13294.0   5026.0  15326.0  2914.0   4441.0   62889.0   9168.0  ...  23057.0  14361.0  14599.0   6925.0  2846.0   8154.0   703.0   783.0   36743.0   52547.0
18 2020-06-01   400.0   3901.0   6902.0   2495.0   6319.0   996.0   1715.0   31467.0   4085.0  ...  17126.0   3120.0   4340.0   2386.0  1570.0   5025.0   513.0   382.0   18020.0   21071.0
19 2020-05-01   186.0   1628.0   5626.0   1521.0   2841.0   457.0    979.0   20787.0   2245.0  ...  13377.0   1106.0   2208.0   1391.0   494.0   3716.0   340.0   191.0    4703.0   16397.0
20 2020-04-01   134.0   1297.0   4708.0    931.0   1936.0   355.0    823.0   17894.0   1974.0  ...  13114.0   1059.0   1600.0   1393.0   295.0   3422.0   369.0   207.0    3726.0   13634.0
21 2020-03-01   862.0  13690.0  16101.0   3551.0  20060.0  2749.0   5807.0   84579.0  14416.0  ...  28254.0  14506.0  17820.0   8349.0  2529.0  19940.0   903.0   811.0   40122.0   96914.0
22 2020-02-01  1667.0  24837.0  22531.0   4923.0  33073.0  4030.0   9417.0  128115.0  22684.0  ...  36181.0  27688.0  25712.0  12360.0  4278.0  27289.0  1256.0  1511.0   60161.0  137542.0
23 2020-01-01  1984.0  25526.0  23595.0   5261.0  34628.0  4422.0  10130.0  132506.0  23224.0  ...  38375.0  29776.0  26492.0  13357.0  4614.0  27758.0  1325.0  1580.0   66067.0  141097.0
24 2019-12-01  2204.0  25704.0  24205.0   5187.0  33464.0  4233.0  11243.0  134607.0  22640.0  ...  35866.0  29886.0  27860.0  13759.0  4792.0  27187.0  1409.0  1747.0   65175.0  148395.0
25 2019-11-01  1983.0  24584.0  24661.0   4931.0  30263.0  4886.0  11019.0  139360.0  24478.0  ...  39602.0  29281.0  27347.0  13367.0  4675.0  29459.0  1375.0  1641.0   68215.0  143007.0
26 2019-10-01  2173.0  28210.0  28315.0   6027.0  36833.0  7826.0  13484.0  175844.0  28961.0  ...  44260.0  33407.0  35370.0  15213.0  5655.0  34250.0  1274.0  1934.0   92012.0  179242.0
27 2019-09-01  2572.0  29329.0  29049.0   9908.0  37735.0  8426.0  15865.0  176614.0  29324.0  ...  43968.0  36534.0  37728.0  16539.0  6418.0  35217.0  2242.0  2917.0   99239.0  186990.0
28 2019-08-01  3012.0  30197.0  29686.0  12911.0  38535.0  9024.0  16373.0  174218.0  29149.0  ...  43548.0  37931.0  40481.0  17583.0  7150.0  32993.0  2726.0  3444.0  110635.0  196632.0
29 2019-07-01  2954.0  30638.0  30711.0  12911.0  39715.0  8895.0  16339.0  178418.0  28525.0  ...  42885.0  37728.0  40453.0  17591.0  7041.0  31426.0  2757.0  3535.0  108069.0  196964.0
30 2019-06-01  2479.0  29954.0  28327.0  10775.0  37872.0  8428.0  15645.0  171786.0  29099.0  ...  43533.0  35891.0  37269.0  16189.0  6103.0  33742.0  2508.0  2937.0   98885.0  189383.0
31 2019-05-01  2262.0  28262.0  28503.0   7053.0  37384.0  7597.0  13281.0  171324.0  28684.0  ...  43880.0  34017.0  36306.0  15470.0  5319.0  34604.0  2555.0  2104.0   86267.0  187445.0
32 2019-04-01  2110.0  27218.0  27080.0   5539.0  36308.0  6305.0  11985.0  158711.0  25866.0  ...  39057.0  30874.0  34229.0  14432.0  4958.0  31597.0  2426.0  1955.0   73548.0  169391.0
33 2019-03-01  1775.0  27362.0  24518.0   5108.0  37157.0  4415.0  11213.0  150008.0  26319.0  ...  41485.0  28338.0  28165.0  13041.0  4299.0  33232.0  2285.0  1848.0   67939.0  157772.0
34 2019-02-01  1625.0  23368.0  21019.0   4529.0  33206.0  3526.0   9256.0  131628.0  22559.0  ...  36782.0  25442.0  24069.0  11906.0  3824.0  28637.0  2022.0  1614.0   59619.0  139353.0
35 2019-01-01  1925.0  24110.0  23694.0   4990.0  35228.0  3751.0  10059.0  138258.0  23211.0  ...  38933.0  27756.0  26258.0  13292.0  4237.0  30192.0  2226.0  1723.0   66304.0  145002.0

[36 rows x 37 columns]

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