如何在Pandas中堆叠数据帧 [英] How to stack data frames on top of each other in Pandas
本文介绍了如何在Pandas中堆叠数据帧的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
df.to_csv（'result.csv'）
out（excel）：
运行1运行2运行3运行4运行5运行6运行7运行8运行9运行10运行11运行12运行13运行14运行15运行15运行16运行17运行18运行19运行20运行21运行22运行23运行24运行25运行26运行27运行28运行29运行30运行31运行32运行33运行34运行35运行36运行37运行38运行39运行40运行41运行42运行43运行44运行45运行46运行47运行48运行49运行50运行51运行52运行53运行54运行55运行56运行57运行58运行59运行60运行61运行62运行63运行64运行65运行66运行67运行68运行69运行70运行71运行72运行73运行74运行75运行76运行77运行78运行79运行80运行81运行82运行83运行84运行85运行86运行87运行88运行89运行运行90运行91运行92运行93运行94运行95运行96运行96
12 5194322.07 5195697.94 5195730.25 5196009.11 519 5054.02 5193386.44 5192664.99 5193381.71 5193652.29 5193637.02 5191110.57 5190267.47 5190739.45 5190416.85 5189592.97 5188898.89 5188461.01 5188735.44 5189156.83 5188870.35 5188306.12 5187746.51 5188023.45 5187536.91 5188085.85 5188634.95 5187861.42 5188124.97 5187076.75 5189218.62 5189052.51 5188571.63 5188486.76 5188502.68 5188318.63 5188512.5 5188409.83 5188250.86 5188885.18 5188999.83 5189365.09 5190159.72 5189771.1 5190136.3 5191179.72 5191256.35 5191147.97 5191712.32 5192430.88 5193407.95 5192603.89 5192248.7 5192197.65 5193096.79 5193005.25 5193451.22 5193985.8 5193489.16 5193562.72 5194621.43 5194170.84 5194198.19 5194866.16 5194030.81 5194421.67 5193745.31 5195458.37 5196342.62 5194881.29 5195036.46 5193627.87 5195017.44 5194470.9 5194402.87 5194659.24 5194751.51 5195016.87 5194802.11 5195467.68 5194654.04 5195622.23 5194709.45 5195050.77 5195097.58 5195987.22 5194776.48 5195831.3 5193605 0.12 5194317.87 5194089.21 5194563.64 5193895.14 5194140.95 5193791.85 5193915.21 5194343.34
13 1453304.43 1454792.33 1454807.96 1454768.09 1455077.49 1454644.59 1454545.94 1454930.93 1455214.85 1455342.12 1455188.92 1454972.08 1455358.05 1455533.45 1455208.56 1454913.89 1455124.45 1454644.83 1455071.25 1454812.46 1454838.9 1454842.33 1454895.52 1454838.55 1454888.25 1455024.08 1454624.57 1455159.29 1454889.65 1454906.92 1454789.36 1454579.06 1455060.12 1455108.26 1455289.8 1455269.54 1455227.93 1455734.55 1455774.16 1455846 1456130.24 1456289.94 1456447.68 1455711.1 1456588.78 1456796.61 1456867.04 1457081.75 1457274.68 1457155.16 1457782.73 1457065.11 1457459.15 1457347.08 1457837.54 1457999.87 1458171.82 1458241.76 1458320.08 1458622.22 1458574.79 1458586.67 1458701.91 1458749.17 1458869.01 1458755.66 1459167.12 1458885 1458881.12 1459110.4 1458918 1459297.49 1459375.28 1459338.09 1459413.22 145 9726.96 1459926.75 1459943.81 1460193.37 1460242.02 1460274.7 1460319.25 1460494.5 1460347.8 1460589.02 1460436.82 1460754.06 1460643.79 1460803.29 1460817.97 1460948.1 1460903.97 1460944.45 1460874.04 1460929.33 1461072.84
14 193379.75 193027.34 192806.25 192501.2 192602.7 192477.86 192402.72 192408.76 192421.74 192400.59 192345.37 192312.98 192331.79 192357.29 192277.84 192270.06 192232.67 192170.09 192216.06 192182.3 192163.13 192145.32 192164.63 192157.59 192134.08 192172.82 192098.36 192146.81 192106.65 192082.12 192057.73 192065.45 192080.46 192128.27 192096.82 192120.97 192081.97 192166.45 192157.38 192121.78 192203.97 192215.73 192098.89 192181.45 192211.12 192234.93 192282.35 192245.5 192290.05 192278.03 192370.19 192250.39 192308.68 192264.65 192339.55 192365.62 192394.12 192385.72 192403.42 192431.52 192414.77 192408.2 192419.74 192424.98 192432.85 192422.79 192444.94 192454.58 192456.89 192449 192451.98 192507.83 192490.77 192504.55 192520.85 192539.33 192549.03 192578.96 192618.21 192638.83 192629.15 192617.57 192651.62 192626.81 192649.6 192636.68 192703.22 192661.42 192687.33 192704.48 192729.77 192731.6 192742.22 192701.82 192729.55 192743.99
15 157553.12 157252.95 157080.77 156941.24 156887.86 156776.95 156669.69 156664.82 156695.03 156652.3 156653.55 156576.01 156586.19 156620.33 156558.26 156501.76 156539 156445.28 156465.98 156435.93 156436.62 156444.92 156422.48 156446.25 156447.14 156426.4 156397.15 156421.85 156391.94 156370.94 156337.46 156364.73 156399.43 156380.6 156389.75 156386.21 156346.02 156453.62 156442.94 156392.71 156436.89 156449.56 156363.24 156448.72 156443.5 156429.21 156479.57 156535.45 156498 156528.7 156603.81 156486.44 156524.97 156482.7 156558.25 156574.41 156585.45 156572.05 156610.77 156638.11 156607.3 156600.19 156626.51 156605.06 156637.24 156611.04 156625.38 156635.17 156644.67 156634.81 156635.81 156690.93 156666.67 156700.49 156702.44 156705.8 156723.19 156746.24 156784.77 156783.37 156816.63 156767.56 156820.49 156805.69 156799.75 156813.77 156847.63 156837.49 156841.06 156833.21 156873.62 156877.83 156877.8 156836.4 156876.97 156889.26
16 98894.09 98661.73 98517.97 98463.94 98381.17 98335.16 98248.41 98271.91 98279.43 98235.13 98240.75 98182.86 98200.03 98172.12 98201.4 98146.85 98131.82 98103.18 98111.26 98089.39 98070.4 98103.34 98063.18 98087.61 98055.12 98101.77 98064.3 98073.7 98044.23 98032.22 98024.03 98035.75 98047.34 98065.01 98070.35 98056.62 98025.54 98091.08 98101.41 98052.04 98079.79 98094.76 98012.52 98088.28 98083.11 98091.65 98097.78 98111.77 98133.52 98135.26 98181.02 98130.98 98142.39 98103.2 98151.5 98163.1 98181.58 98161.11 98181.91 98207.14 98176.71 98194 98203.63 98178.89 98213.34 98179.43 98188.91 98209 98224.92 98202.98 98199.12 98239.48 98228.15 98251.45 98263.44 98253.43 98253.53 98293.22 98310.56 98299.46 98324.44 98304.57 98320.92 98331.45 98315.52 98316.35 98350.96 98356.69 98336.74 98322.17 98356.82 98367.58 98355.18 98342.84 98346.7 98374.95
17
12 3129.52 3147.16 3160.49 3171.33 3214.77 3236.69 3275 3280.86 3287.46 3302.41 3331.16 3375.36 3371.95 3378.69 3377.02 3373.65 3397.39 3388.79 3416.8 3457.74 3447.79 3456.51 3455.32 3495.66 3492.27 3505.96 3510.87 3533.18 3522.81 3524.65 3572.99 3575.17 3581.11 3579.16 3584.39 3601.6 3591.13 3619.1 3581.45 3597.28 3610.98 3627.1 3641.58 3639.8 3628.65 3655.72 3649.4 3648.33 3676.89 3661.96 3697.21 3689.05 3693.71 3710.29 3734.39 3732.68 3732.57 3760.45 3753.94 3778.77 3792.45 3764.17 3804.36 3804.46 3807.49 3817.46 3854.72 3820.18 3844.23 3844.19 3856.38 3856.53 3856.95 3905.39 3868.66 3898.41 3908.94 3905.1 3942.19 3941.65 3957.9 3936.05 3953.8 3952.5 3986.09 3972.33 3974.86 3962.69 4006.6 4007.01 4013.11 4036.94 3981.75 3982.69 3982.16 4017.66
13 2946817.59 2944662.04 2941123.24 2940256.46 2935558.38 2931746.01 2928978.21 2928741.48 2926931.72 2926556.07 2924090.79 2923586 2923616.24 2921712.71 2921325.33 2921606.4 2921049.04 2920501.43 2920219.82 2919483.39 2919055.94 2918261.89 2917710.17 2918281.08 2917460.36 2918447.78 2917467.81 2917025.06 2914725.09 2917582.26 2916970.03 2917224.28 2917123.34 2916758.73 2916377.49 2916374.34 2915134.44 2916170.14 2916194.3 2916438.93 2916841.46 2916923.27 2916298.61 2916843.73 2917128.84 2916505.26 2917823.72 2917249.33 2918275.17 2918657.92 2918593.87 2918092.17 2916450.26 2917383.96 2917260.84 2918251.2 2916669.62 2917421.6 2916740.6 2917259.97 2916818.62 2917508.43 2918006.44 2917757.21 2918060.88 2915855.65 2918151.83 2917179.65 2918271.42 2917682.08 2916751.82 2916528.9 2916524.81 2916802.18 2915576.36 2916073.58 2916285.37 2915885.03 2916843.4 2916897 2916226.64 2915110.13 2916329.2 2916433.5 2914458.88 2915075.24 2915229.63 2913743.19 2914563.32 2913637.85 2914569.65 2914736.45 2913404.01 2913008.04 2913627.33 2914075.7
14 2 30608.01 230312.12 229832.18 229627.99 229210.49 228632.32 228363.82 228331.31 228218.46 228144.81 227964.12 227953.21 228026.95 227840.86 227741.13 227753.98 227740.91 227540.28 227557.01 227318.88 227512.95 227296.66 227285.16 227307.5 227240.68 227426.04 227221.35 227178.03 226972.82 227183.08 227053.52 227103.26 227226.78 227095.99 227295.09 227357.08 226998.07 227155.45 227099.14 227256.82 227092.64 227274.71 227046.17 227211.35 227271.17 227113.9 227296.57 227410.79 227169.76 227314.2 227496.21 227252.71 227267.55 227308.58 227361.06 227333.64 227178.12 227358.18 227154.37 227278.39 227226.46 227220.65 227276.21 227336.72 227239.63 227201.77 227286.38 227298.1 227398.71 227336.91 227365.81 227241.09 227255.2 227129.99 227074.28 227152.61 227331.13 227349.15 227404.26 227317.63 227228.69 227163.85 226953.01 22692 2.52 227207.38 227141.31 227117.31 227162.19 227210.19 227078.05 227066.16 227226.41 226951.75 226963.37 226956.1 227106.71
15 25607.66 25705.26 25483.12 25478.82 25410.26 25384.14 25296.8 25297.31 25185.21 25310.15 25275.49 25246.13 25249.32 25322.94 25258.49 25231.09 25294.81 25282.72 25211.84 25373.49 25201.84 25277.95 25356.21 25331.92 25191.69 25268.33 25359.69 25177.89 25275.49 25293.96 25212.5 25256.51 25209.77 25207.68 25245.21 25130.97 25246.49 25073.61 25141.74 25191.55 25275.35 25218.04 25234.66 25144.64 25294.39 25197.99 25252.66 25029.12 25239.01 25241.82 25299.99 25249.92 25112.44 25140.67 25247.73 25235.76 25316.81 25122.93 25188.8 25186.04 25149.75 25127.59 25175.98 25224.16 25093.1 25166.84 25170.27 25258.65 25203.5 25192.54 25154.19 25180.35 25197.78 25340.6 25224.43 25173.91 25205.17 25253.24 25325.32 25457.4 25186.6 25238.33 25237.85 25130.99 25303.22 25188.74 25226.41 25190.27 25082.58 25059.87 25295.12 25197.11 25222.02 25208.2 25173.89 25197.88
对不起（从excel复制），标签和数据不符合。
基本上，我想将这个数据框分开为8个单位...所以对于第一个单元，单元1，我想要12列....运行1到12 。 等等。单元8将运行85 - 96.
我刚刚重命名了8个数据帧，并指定了我想从主数据框（df）中获取的列
这是我的代码：
df1 = df.ix [：，0： 7]
df2 = df.ix [：，12:24]
df3 = df.ix [：，24:36]
df4 = df.ix [：，36:48]
df5 = df.ix [：，48:60]
df6 = df.ix [：，60:72]
df7 = df.ix [：，72:84]
df8 = df.ix [：，84:96]
pieces =（df1，df2，df3，df4，df5，df6，df7，df8）
最后，我使用concat将8个数据帧连接在一起（堆叠在一起）。但是，输出有些扭曲，并不顺序。
df_final = pd.concat（pieces，ignore_index = True）
打印df_final
out：
运行1运行13运行14运行15运行16运行17运行18运行19运行2运行20运行21运行22运行23运行24运行25运行26运行27运行28运行29运行3运行30运行30运行31运行32运行33运行34执行35运行36运行37运行38运行39运行4运行40运行41运行42运行43运行44运行45运行46运行47运行48运行49运行49运行5运行50运行51运行52运行53运行54运行55运行56运行57运行58运行59运行6运行60运行61运行62运行63运行64运行65运行66运行67运行68运行69运行7运行70运行71运行72运行73运行73运行74运行75运行76运行77运行78运行79运行80运行81运行82运行83运行84运行85运行86运行87运行88运行89运行90运行91运行92运行93运行94运行95运行96运行96
0 5194322.07 5195697.94 5195730.25 5196009.11 5195054.02 5193386.44 5192664.99
1 1453304.43 1454792.33 1454807.96 1454768.09 1455077.49 1454644.59 1454545.94
2 193379.75 193027.34 192806.25 192501.2 192602.7 192477.86 192402.72
3 157553.12 157252.95 157080.77 156941.24 156887.86 156776.95 156669.69
4 98894.09 98661.73 98517.97 98463.94 98381.17 98335.16 98248.41
5
6 3129.52 3147.16 3160.49 3171.33 3214.77 3236.69 3275
7 2946817.59 2944662.04 2941123.24 2940256.46 2935558.38 2931746.01 2928978.21
8 230608.01 230312.12 229832.18 229627.99 229210.49 228632.32 228363.82
9 25607.66 25705.26 25483.12 25478.82 25410.26 25384.14 25296.8
10 5190739.45 5190416.85 5189592.97 5188898.89 5188461.01 5188735.44 5189156.83 5188870.35 5188306.12 5187746.51 5188023.45 5187536.91
11 1455358.05 1455533.45 1455208.56 1454913.89 1455124.45 1454644.83 1455071.25 1454812.46 1454838.9 1454842.33 1454895.52 1454838.55
12 192331.79 192357.29 192277.84 192270.06 192232.67 192170.09 192216.06 192182.3 192163.13 192145.32 192164.63 192157.59
13 156586.19 156620.33 156558.26 156539 156501.76 156445.28 156465.98 156435.93 156436.62 156444.92 156422.48 156446.25
14 98200.03 98201.4 98172.12 98146.85 98131.82 98103.18 98111.26 98070.4 98089.39 98103.34 98063.18 98087.61
15
16 3371.95 3378.69 3377.02 3373.65 3397.39 3388.79 3416.8 3457.74 3447.79 3456.51 3455.32 3495.66
17 2923616.24 2921712.71 2921325.33 2921606.4 2921049.04 2920501.43 2920219.82 2919483.39 2919055.94 2918261.89 2917710.17 2918281.08
18 228026.95 227840.86 227741.13 227753.98 227740.91 227540.28 227557.01 227318.88 227512.95 227296.66 227285.16 227307.5
19 25249.32 25322.94 25258.49 25231.09 25294.81 25282.72 25211.84 25373.49 25201.84 25277.95 25356.21 25331.92
20 5188085.85 5188634.95 5187861.42 5188124.97 5187076.75 5189218.62 5189052.51 5188571.63 5188486.76 5188502.68 5188318.63 5188512.5
21 1454888.25 1455024.08 1454624.57 1455159.29 1454889.65 1454906.92 1454789.36 1454579.06 1455060.12 1455108.26 1455289.8 1455269.54
22 192134.08 192172.82 192098.36 192146.81 192106.65 192082.12 192057.73 192065.45 192080.46 192128.27 192096.82 192120.97
23 156426.4 156447.14 156397.15 156421.85 156391.94 156370.94 156337.46 156364.73 156380.6 156399.43 156389.75 156386.21
24 98055.12 98101.77 98064.3 98073.7 98044.23 98032.22 98024.03 98035.75 98047.34 98065.01 98070.35 98056.62
25
26 3492.27 3505.96 3510.87 3533.18 3522.81 3524.65 3572.99 3575.17 3581.11 3579.16 3584.39 3601.6
27 2917460.36 2918447.78 2917467.81 2917025.06 2914725.09 2917582.26 2916970.03 2917224.28 2917123.34 2916758.73 2916377.49 2916374.34
28 227240.68 227426.04 227221.35 227178.03 226972.82 227183.08 227053.52 227103.26 227226.78 227095.99 227295.09 227357.08
29 25191.69 25268.33 25359.69 25177.89 25275.49 25293.96 25212.5 25256.51 25209.77 25207.68 25245.21 25130.97
30 5188409.83 5188250.86 5188885.18 5188999.83 5189365.09 5190159.72 5189771.1 5190136.3 5191179.72 5191256.35 5191147.97 5191712.32
31 1455227.93 1455734.55 1455846 1455774.16 1456130.24 1456289.94 1455711.1 1456447.68 1456588.78 1456796.61 1456867.04 1457081.75
32 192081.97 192166.45 192157.38 192121.78 192203.97 192215.73 192098.89 192181.45 192211.12 192234.93 192245.5 192282.35
33 156346.02 156453.62 156442.94 156392.71 156436.89 156449.56 156363.24 156443.5 156448.72 156429.21 156479.57 156498
34 98025.54 98091.08 98101.41 98052.04 98079.79 98094.76 98012.52 98088.28 98083.11 98091.65 98097.78 98111.77
35
36 3591.13 3619.1 3581.45 3597.28 3610.98 3627.1 3641.58 3639.8 3628.65 3655.72 3649.4 3648.33
37 2915134.44 2916170.14 2916194.3 2916438.93 2916841.46 2916923.27 2916298.61 2916843.73 2917128.84 2916505.26 2917823.72 2917249.33
38 226998.07 227155.45 227099.14 227256.82 227092.64 227274.71 227046.17 227211.35 227271.17 227113.9 227296.57 227410.79
39 25246.49 25073.61 25141.74 25191.55 25275.35 25218.04 25234.66 25144.64 25294.39 25197.99 25252.66 25029.12
40 5192430.88 5193407.95 5192603.89 5192248.7 5192197.65 5193096.79 5193005.25 5193985.8 5193451.22 5193489.16 5193562.72 5194621.43
41 1457274.68 1457155.16 1457782.73 1457065.11 1457459.15 1457347.08 1457837.54 1457999.87 1458171.82 1458241.76 1458320.08 1458622.22
42 192290.05 192278.03 192370.19 192250.39 192308.68 192264.65 192339.55 192365.62 192394.12 192385.72 192403.42 192431.52
43 156535.45 156528.7 156603.81 156486.44 156524.97 156482.7 156558.25 156574.41 156585.45 156572.05 156610.77 156638.11
44 98133.52 98135.26 98181.02 98130.98 98142.39 98103.2 98151.5 98163.1 98181.58 98161.11 98181.91 98207.14
45
46 3676.89 3661.96 3697.21 3689.05 3693.71 3710.29 3734.39 3732.68 3732.57 3760.45 3753.94 3778.77
47 2918275.17 2918657.92 2918593.87 2918092.17 2916450.26 2917383.96 2917260.84 2918251.2 2916669.62 2917421.6 2916740.6 2917259.97
48 227169.76 227314.2 227496.21 227252.71 227267.55 227308.58 227361.06 227333.64 227178.12 227358.18 227154.37 227278.39
49 25239.01 25241.82 25299.99 25249.92 25112.44 25140.67 25247.73 25235.76 25316.81 25188.8 25122.93 25186.04
50 5194170.84 5194198.19 5194866.16 5194030.81 5194421.67 5193745.31 5195458.37 5196342.62 5194881.29 5195036.46 5193627.87 5194470.9
51 1458574.79 1458586.67 1458701.91 1458749.17 1458869.01 1458755.66 1458885 1459167.12 1458881.12 1459110.4 1458918 1459297.49
52 192408.2 192414.77 192419.74 192424.98 192432.85 192422.79 192444.94 192454.58 192456.89 192449 192451.98 192507.83
53 156607.3 156600.19 156626.51 156605.06 156637.24 156611.04 156625.38 156635.17 156644.67 156634.81 156635.81 156690.93
54 98176.71 98194 98203.63 98178.89 98213.34 98179.43 98188.91 98209 98224.92 98202.98 98199.12 98239.48
55
56 3792. 45 3764.17 3804.36 3804.46 3807.49 3817.46 3854.72 3820.18 3844.23 3844.19 3856.38 3856.53
57 2916818.62 2917508.43 2918006.44 2917757.21 2918060.88 2915855.65 2918151.83 2917179.65 2918271.42 2917682.08 2916528.9 2916751.82
58 227226.46 227220.65 227276.21 227336.72 227239.63 227201.77 227298.1 227286.38 227398.71 227336.91 227365.81 227255.2
59 25149.75 25127.59 25175.98 25093.1 25224.16 25166.84 25170.27 25203.5 25258.65 25192.54 25154.19 25180.35
60 5195017.44 5194402.87 5194659.24 5194751.51 5195016.87 5194802.11 5195467.68 5194654.04 5195622.23 5194709.45 5195050.77 5195097.58
61 1459375.28 1459338.09 1459413.22 1459726.96 1459926.75 1459943.81 1460193.37 1460242.02 1460274.7 1460319.25 1460494.5 1460347.8
62 192490.77 192504.55 192520.85 192539.33 192549.03 192578.96 192618.21 192638.83 192629.15 192617.57 192651.62 192626.81
63 156666.67 156700.49 156702.44 156705.8 156723.19 156746.24 156784.77 156783.37 156816.63 156767.56 156820.49 156805.69
64 98228.15 98251.45 98263.44 98253.43 98253.53 98293.22 98310.56 98299.46 98324.44 98304.57 98320.92 98331.45
65
66 3856.95 3905.39 3868.66 3898.41 3908.94 3905.1 3942.19 3941.65 3957.9 3936.05 3953.8 3952.5
67 2916524.81 2916802.18 291 5576.36 2916073.58 2916285.37 2915885.03 2916843.4 2916897 2916226.64 2916329.2 2915110.13 2914458.88
68 227241.09 227129.99 227074.28 227152.61 227331.13 227349.15 227404.26 227317.63 227228.69 227163.85 226953.01 226922.52
69 25197.78 25340.6 25224.43 25173.91 25205.17 25253.24 25325.32 25459.4 25186.6 252 38.33 25237.85 25130.99
70 5195987.22 5195831.3 5194776.48 5193605.12 5194317.87 5194089.21 5194563.64 5193895.14 5194140.95 5193791.85 5193915.21 5194343.34
71 1460589.02 1460436.82 1460754.06 1460643.79 1460803.29 1460817.97 1460948.1 1460903.97 1460944.45 1460874.04 1460929.3 3 1461072.84
72 192649.6 192636.68 192703.22 192661.42 192687.33 192704.48 192729.77 192731.6 192742.22 192701.82 192729.55 192743.99
73 156799.75 156813.77 156847.63 156837.49 156841.06 156833.21 156873.62 156877.83 156877.8 156836.4 156876.97 156889.26
74 98315.52 98316.35 98350.96 98356.69 98336.74 98322.17 98356.82 98367.58 98355.18 98342.84 98346.7 98374.95
75
76 3986.09 3972.33 3974.86 3962.69 4006.6 4007.01 4013.11 4036.94 3981.75 3982.69 3982.16 4017.66
77 2916433.5 2915075.24 2915229.63 2913743.19 2914563.32 2913637.85 2914569.65 2914736.45 2913404.01 2913008.04 2913627.33 2914075.7
78 227207. 38 227141.31 227117.31 227162.19 227210.19 227078.05 227066.16 227226.41 226951.75 226963.37 226956.1 227106.71
79 25303.22 25188.74 25226.41 25190.27 25082.58 25059.87 25295.12 25197.11 25222.02 25208.2 25173.89 25197.88
This is my problem. I want the dataframes in line and stacked on top of each other.
解决方案
You’re very nearly there.
The problem is that the column names are all different within each sub dataframe. Thus, when pandas does the concat, it doesn’t just append the dataframes to the bottom, it expands the dataframe to have new colums with the right names and then appends the rows.
You can solve this by renaming the columns in the sub dataframes e.g.
for sub_df in pieces:
sub_df.columns=range(12)
N.B. df2 to df8 contain what you want, I think. For some reason, you’ve made df1 contain only the first 7 columns, rather than 12. I’ll assume that’s a typo for now.
Resulting in full working code (I copied your input data into a file named ’data1.csv’)
import pandas as pd
import numpy as np
df = pd.read_csv(’data1.csv’)
df1 = df.ix[:,0:12]
df2 = df.ix[:,12:24]
df3 = df.ix[:,24:36]
df4 = df.ix[:,36:48]
df5 = df.ix[:,48:60]
df6 = df.ix[:,60:72]
df7 = df.ix[:,72:84]
df8 = df.ix[:,84:96]
pieces = (df1,df2,df3,df4,df5,df6,df7,df8)
# Give the columns the same labels in each sub dataframe
# I’ve used numbers for convenience - you can give more descriptive names if you want
for sub_df in pieces:
sub_df.columns=range(12)
df_final = pd.concat(pieces, ignore_index = True)
print df_final
Final no te on ordering
You note the unexpected ordering of your columns in your example. This won’t affect my solution, but I will explain it for completeness.
The columns in your output are in what is called ’Lexicographic ordering’. This is a common problem when sorting strings containing numbers in Python (and other languages). They are sorted in an order that looks almost right, but somehow runs 1, 10, 11 ... 19, 2, 20 and so on. That is because the ordering sorts letter by letter like a dictionary, but with 0 to 9 coming before a
I have a dataframe with 96 columns:
df.to_csv('result.csv')
out (excel):
Run 1 Run 2 Run 3 Run 4 Run 5 Run 6 Run 7 Run 8 Run 9 Run 10 Run 11 Run 12 Run 13 Run 14 Run 15 Run 16 Run 17 Run 18 Run 19 Run 20 Run 21 Run 22 Run 23 Run 24 Run 25 Run 26 Run 27 Run 28 Run 29 Run 30 Run 31 Run 32 Run 33 Run 34 Run 35 Run 36 Run 37 Run 38 Run 39 Run 40 Run 41 Run 42 Run 43 Run 44 Run 45 Run 46 Run 47 Run 48 Run 49 Run 50 Run 51 Run 52 Run 53 Run 54 Run 55 Run 56 Run 57 Run 58 Run 59 Run 60 Run 61 Run 62 Run 63 Run 64 Run 65 Run 66 Run 67 Run 68 Run 69 Run 70 Run 71 Run 72 Run 73 Run 74 Run 75 Run 76 Run 77 Run 78 Run 79 Run 80 Run 81 Run 82 Run 83 Run 84 Run 85 Run 86 Run 87 Run 88 Run 89 Run 90 Run 91 Run 92 Run 93 Run 94 Run 95 Run 96
12 5194322.07 5195697.94 5195730.25 5196009.11 5195054.02 5193386.44 5192664.99 5193381.71 5193652.29 5193637.02 5191110.57 5190267.47 5190739.45 5190416.85 5189592.97 5188898.89 5188461.01 5188735.44 5189156.83 5188870.35 5188306.12 5187746.51 5188023.45 5187536.91 5188085.85 5188634.95 5187861.42 5188124.97 5187076.75 5189218.62 5189052.51 5188571.63 5188486.76 5188502.68 5188318.63 5188512.5 5188409.83 5188250.86 5188885.18 5188999.83 5189365.09 5190159.72 5189771.1 5190136.3 5191179.72 5191256.35 5191147.97 5191712.32 5192430.88 5193407.95 5192603.89 5192248.7 5192197.65 5193096.79 5193005.25 5193985.8 5193451.22 5193489.16 5193562.72 5194621.43 5194170.84 5194198.19 5194866.16 5194030.81 5194421.67 5193745.31 5195458.37 5196342.62 5194881.29 5195036.46 5193627.87 5194470.9 5195017.44 5194402.87 5194659.24 5194751.51 5195016.87 5194802.11 5195467.68 5194654.04 5195622.23 5194709.45 5195050.77 5195097.58 5195987.22 5195831.3 5194776.48 5193605.12 5194317.87 5194089.21 5194563.64 5193895.14 5194140.95 5193791.85 5193915.21 5194343.34
13 1453304.43 1454792.33 1454807.96 1454768.09 1455077.49 1454644.59 1454545.94 1454930.93 1455214.85 1455342.12 1455188.92 1454972.08 1455358.05 1455533.45 1455208.56 1454913.89 1455124.45 1454644.83 1455071.25 1454812.46 1454838.9 1454842.33 1454895.52 1454838.55 1454888.25 1455024.08 1454624.57 1455159.29 1454889.65 1454906.92 1454789.36 1454579.06 1455060.12 1455108.26 1455289.8 1455269.54 1455227.93 1455734.55 1455846 1455774.16 1456130.24 1456289.94 1455711.1 1456447.68 1456588.78 1456796.61 1456867.04 1457081.75 1457274.68 1457155.16 1457782.73 1457065.11 1457459.15 1457347.08 1457837.54 1457999.87 1458171.82 1458241.76 1458320.08 1458622.22 1458574.79 1458586.67 1458701.91 1458749.17 1458869.01 1458755.66 1458885 1459167.12 1458881.12 1459110.4 1458918 1459297.49 1459375.28 1459338.09 1459413.22 1459726.96 1459926.75 1459943.81 1460193.37 1460242.02 1460274.7 1460319.25 1460494.5 1460347.8 1460589.02 1460436.82 1460754.06 1460643.79 1460803.29 1460817.97 1460948.1 1460903.97 1460944.45 1460874.04 1460929.33 1461072.84
14 193379.75 193027.34 192806.25 192501.2 192602.7 192477.86 192402.72 192408.76 192421.74 192400.59 192345.37 192312.98 192331.79 192357.29 192277.84 192270.06 192232.67 192170.09 192216.06 192182.3 192163.13 192145.32 192164.63 192157.59 192134.08 192172.82 192098.36 192146.81 192106.65 192082.12 192057.73 192065.45 192080.46 192128.27 192096.82 192120.97 192081.97 192166.45 192157.38 192121.78 192203.97 192215.73 192098.89 192181.45 192211.12 192234.93 192245.5 192282.35 192290.05 192278.03 192370.19 192250.39 192308.68 192264.65 192339.55 192365.62 192394.12 192385.72 192403.42 192431.52 192408.2 192414.77 192419.74 192424.98 192432.85 192422.79 192444.94 192454.58 192456.89 192449 192451.98 192507.83 192490.77 192504.55 192520.85 192539.33 192549.03 192578.96 192618.21 192638.83 192629.15 192617.57 192651.62 192626.81 192649.6 192636.68 192703.22 192661.42 192687.33 192704.48 192729.77 192731.6 192742.22 192701.82 192729.55 192743.99
15 157553.12 157252.95 157080.77 156941.24 156887.86 156776.95 156669.69 156664.82 156695.03 156652.3 156653.55 156576.01 156586.19 156620.33 156558.26 156539 156501.76 156445.28 156465.98 156435.93 156436.62 156444.92 156422.48 156446.25 156426.4 156447.14 156397.15 156421.85 156391.94 156370.94 156337.46 156364.73 156380.6 156399.43 156389.75 156386.21 156346.02 156453.62 156442.94 156392.71 156436.89 156449.56 156363.24 156443.5 156448.72 156429.21 156479.57 156498 156535.45 156528.7 156603.81 156486.44 156524.97 156482.7 156558.25 156574.41 156585.45 156572.05 156610.77 156638.11 156607.3 156600.19 156626.51 156605.06 156637.24 156611.04 156625.38 156635.17 156644.67 156634.81 156635.81 156690.93 156666.67 156700.49 156702.44 156705.8 156723.19 156746.24 156784.77 156783.37 156816.63 156767.56 156820.49 156805.69 156799.75 156813.77 156847.63 156837.49 156841.06 156833.21 156873.62 156877.83 156877.8 156836.4 156876.97 156889.26
16 98894.09 98661.73 98517.97 98463.94 98381.17 98335.16 98248.41 98271.91 98279.43 98235.13 98240.75 98182.86 98200.03 98201.4 98172.12 98146.85 98131.82 98103.18 98111.26 98070.4 98089.39 98103.34 98063.18 98087.61 98055.12 98101.77 98064.3 98073.7 98044.23 98032.22 98024.03 98035.75 98047.34 98065.01 98070.35 98056.62 98025.54 98091.08 98101.41 98052.04 98079.79 98094.76 98012.52 98088.28 98083.11 98091.65 98097.78 98111.77 98133.52 98135.26 98181.02 98130.98 98142.39 98103.2 98151.5 98163.1 98181.58 98161.11 98181.91 98207.14 98176.71 98194 98203.63 98178.89 98213.34 98179.43 98188.91 98209 98224.92 98202.98 98199.12 98239.48 98228.15 98251.45 98263.44 98253.43 98253.53 98293.22 98310.56 98299.46 98324.44 98304.57 98320.92 98331.45 98315.52 98316.35 98350.96 98356.69 98336.74 98322.17 98356.82 98367.58 98355.18 98342.84 98346.7 98374.95
17
12 3129.52 3147.16 3160.49 3171.33 3214.77 3236.69 3275 3280.86 3287.46 3302.41 3331.16 3375.36 3371.95 3378.69 3377.02 3373.65 3397.39 3388.79 3416.8 3457.74 3447.79 3456.51 3455.32 3495.66 3492.27 3505.96 3510.87 3533.18 3522.81 3524.65 3572.99 3575.17 3581.11 3579.16 3584.39 3601.6 3591.13 3619.1 3581.45 3597.28 3610.98 3627.1 3641.58 3639.8 3628.65 3655.72 3649.4 3648.33 3676.89 3661.96 3697.21 3689.05 3693.71 3710.29 3734.39 3732.68 3732.57 3760.45 3753.94 3778.77 3792.45 3764.17 3804.36 3804.46 3807.49 3817.46 3854.72 3820.18 3844.23 3844.19 3856.38 3856.53 3856.95 3905.39 3868.66 3898.41 3908.94 3905.1 3942.19 3941.65 3957.9 3936.05 3953.8 3952.5 3986.09 3972.33 3974.86 3962.69 4006.6 4007.01 4013.11 4036.94 3981.75 3982.69 3982.16 4017.66
13 2946817.59 2944662.04 2941123.24 2940256.46 2935558.38 2931746.01 2928978.21 2928741.48 2926931.72 2926556.07 2924090.79 2923586 2923616.24 2921712.71 2921325.33 2921606.4 2921049.04 2920501.43 2920219.82 2919483.39 2919055.94 2918261.89 2917710.17 2918281.08 2917460.36 2918447.78 2917467.81 2917025.06 2914725.09 2917582.26 2916970.03 2917224.28 2917123.34 2916758.73 2916377.49 2916374.34 2915134.44 2916170.14 2916194.3 2916438.93 2916841.46 2916923.27 2916298.61 2916843.73 2917128.84 2916505.26 2917823.72 2917249.33 2918275.17 2918657.92 2918593.87 2918092.17 2916450.26 2917383.96 2917260.84 2918251.2 2916669.62 2917421.6 2916740.6 2917259.97 2916818.62 2917508.43 2918006.44 2917757.21 2918060.88 2915855.65 2918151.83 2917179.65 2918271.42 2917682.08 2916528.9 2916751.82 2916524.81 2916802.18 2915576.36 2916073.58 2916285.37 2915885.03 2916843.4 2916897 2916226.64 2916329.2 2915110.13 2914458.88 2916433.5 2915075.24 2915229.63 2913743.19 2914563.32 2913637.85 2914569.65 2914736.45 2913404.01 2913008.04 2913627.33 2914075.7
14 230608.01 230312.12 229832.18 229627.99 229210.49 228632.32 228363.82 228331.31 228218.46 228144.81 227964.12 227953.21 228026.95 227840.86 227741.13 227753.98 227740.91 227540.28 227557.01 227318.88 227512.95 227296.66 227285.16 227307.5 227240.68 227426.04 227221.35 227178.03 226972.82 227183.08 227053.52 227103.26 227226.78 227095.99 227295.09 227357.08 226998.07 227155.45 227099.14 227256.82 227092.64 227274.71 227046.17 227211.35 227271.17 227113.9 227296.57 227410.79 227169.76 227314.2 227496.21 227252.71 227267.55 227308.58 227361.06 227333.64 227178.12 227358.18 227154.37 227278.39 227226.46 227220.65 227276.21 227336.72 227239.63 227201.77 227298.1 227286.38 227398.71 227336.91 227365.81 227255.2 227241.09 227129.99 227074.28 227152.61 227331.13 227349.15 227404.26 227317.63 227228.69 227163.85 226953.01 226922.52 227207.38 227141.31 227117.31 227162.19 227210.19 227078.05 227066.16 227226.41 226951.75 226963.37 226956.1 227106.71
15 25607.66 25705.26 25483.12 25478.82 25410.26 25384.14 25296.8 25297.31 25185.21 25310.15 25275.49 25246.13 25249.32 25322.94 25258.49 25231.09 25294.81 25282.72 25211.84 25373.49 25201.84 25277.95 25356.21 25331.92 25191.69 25268.33 25359.69 25177.89 25275.49 25293.96 25212.5 25256.51 25209.77 25207.68 25245.21 25130.97 25246.49 25073.61 25141.74 25191.55 25275.35 25218.04 25234.66 25144.64 25294.39 25197.99 25252.66 25029.12 25239.01 25241.82 25299.99 25249.92 25112.44 25140.67 25247.73 25235.76 25316.81 25188.8 25122.93 25186.04 25149.75 25127.59 25175.98 25093.1 25224.16 25166.84 25170.27 25203.5 25258.65 25192.54 25154.19 25180.35 25197.78 25340.6 25224.43 25173.91 25205.17 25253.24 25325.32 25459.4 25186.6 25238.33 25237.85 25130.99 25303.22 25188.74 25226.41 25190.27 25082.58 25059.87 25295.12 25197.11 25222.02 25208.2 25173.89 25197.88
sorry (copied from excel), the labels and data are not in line.
Basically, I want to seperate this dataframe into 8 units... so for the first unit, Unit 1, I want 12 columns.... runs 1 to 12. and so on. Unit 8 will be run 85 - 96.
I just renamed 8 dataframes and specified the columns I wanted to take from the main dataframe (df)
Here is my code for this:
df1 = df.ix[:,0:7]
df2 = df.ix[:,12:24]
df3 = df.ix[:,24:36]
df4 = df.ix[:,36:48]
df5 = df.ix[:,48:60]
df6 = df.ix[:,60:72]
df7 = df.ix[:,72:84]
df8 = df.ix[:,84:96]
pieces = (df1,df2,df3,df4,df5,df6,df7,df8)
Finally, I used concat to concatenate the 8 dataframes together (Stacked on top of each other). However, the output it somewhat distorted and it is not in order.
df_final = pd.concat(pieces, ignore_index = True)
print df_final
out:
Run 1 Run 13 Run 14 Run 15 Run 16 Run 17 Run 18 Run 19 Run 2 Run 20 Run 21 Run 22 Run 23 Run 24 Run 25 Run 26 Run 27 Run 28 Run 29 Run 3 Run 30 Run 31 Run 32 Run 33 Run 34 Run 35 Run 36 Run 37 Run 38 Run 39 Run 4 Run 40 Run 41 Run 42 Run 43 Run 44 Run 45 Run 46 Run 47 Run 48 Run 49 Run 5 Run 50 Run 51 Run 52 Run 53 Run 54 Run 55 Run 56 Run 57 Run 58 Run 59 Run 6 Run 60 Run 61 Run 62 Run 63 Run 64 Run 65 Run 66 Run 67 Run 68 Run 69 Run 7 Run 70 Run 71 Run 72 Run 73 Run 74 Run 75 Run 76 Run 77 Run 78 Run 79 Run 80 Run 81 Run 82 Run 83 Run 84 Run 85 Run 86 Run 87 Run 88 Run 89 Run 90 Run 91 Run 92 Run 93 Run 94 Run 95 Run 96
0 5194322.07 5195697.94 5195730.25 5196009.11 5195054.02 5193386.44 5192664.99
1 1453304.43 1454792.33 1454807.96 1454768.09 1455077.49 1454644.59 1454545.94
2 193379.75 193027.34 192806.25 192501.2 192602.7 192477.86 192402.72
3 157553.12 157252.95 157080.77 156941.24 156887.86 156776.95 156669.69
4 98894.09 98661.73 98517.97 98463.94 98381.17 98335.16 98248.41
5
6 3129.52 3147.16 3160.49 3171.33 3214.77 3236.69 3275
7 2946817.59 2944662.04 2941123.24 2940256.46 2935558.38 2931746.01 2928978.21
8 230608.01 230312.12 229832.18 229627.99 229210.49 228632.32 228363.82
9 25607.66 25705.26 25483.12 25478.82 25410.26 25384.14 25296.8
10 5190739.45 5190416.85 5189592.97 5188898.89 5188461.01 5188735.44 5189156.83 5188870.35 5188306.12 5187746.51 5188023.45 5187536.91
11 1455358.05 1455533.45 1455208.56 1454913.89 1455124.45 1454644.83 1455071.25 1454812.46 1454838.9 1454842.33 1454895.52 1454838.55
12 192331.79 192357.29 192277.84 192270.06 192232.67 192170.09 192216.06 192182.3 192163.13 192145.32 192164.63 192157.59
13 156586.19 156620.33 156558.26 156539 156501.76 156445.28 156465.98 156435.93 156436.62 156444.92 156422.48 156446.25
14 98200.03 98201.4 98172.12 98146.85 98131.82 98103.18 98111.26 98070.4 98089.39 98103.34 98063.18 98087.61
15
16 3371.95 3378.69 3377.02 3373.65 3397.39 3388.79 3416.8 3457.74 3447.79 3456.51 3455.32 3495.66
17 2923616.24 2921712.71 2921325.33 2921606.4 2921049.04 2920501.43 2920219.82 2919483.39 2919055.94 2918261.89 2917710.17 2918281.08
18 228026.95 227840.86 227741.13 227753.98 227740.91 227540.28 227557.01 227318.88 227512.95 227296.66 227285.16 227307.5
19 25249.32 25322.94 25258.49 25231.09 25294.81 25282.72 25211.84 25373.49 25201.84 25277.95 25356.21 25331.92
20 5188085.85 5188634.95 5187861.42 5188124.97 5187076.75 5189218.62 5189052.51 5188571.63 5188486.76 5188502.68 5188318.63 5188512.5
21 1454888.25 1455024.08 1454624.57 1455159.29 1454889.65 1454906.92 1454789.36 1454579.06 1455060.12 1455108.26 1455289.8 1455269.54
22 192134.08 192172.82 192098.36 192146.81 192106.65 192082.12 192057.73 192065.45 192080.46 192128.27 192096.82 192120.97
23 156426.4 156447.14 156397.15 156421.85 156391.94 156370.94 156337.46 156364.73 156380.6 156399.43 156389.75 156386.21
24 98055.12 98101.77 98064.3 98073.7 98044.23 98032.22 98024.03 98035.75 98047.34 98065.01 98070.35 98056.62
25
26 3492.27 3505.96 3510.87 3533.18 3522.81 3524.65 3572.99 3575.17 3581.11 3579.16 3584.39 3601.6
27 2917460.36 2918447.78 2917467.81 2917025.06 2914725.09 2917582.26 2916970.03 2917224.28 2917123.34 2916758.73 2916377.49 2916374.34
28 227240.68 227426.04 227221.35 227178.03 226972.82 227183.08 227053.52 227103.26 227226.78 227095.99 227295.09 227357.08
29 25191.69 25268.33 25359.69 25177.89 25275.49 25293.96 25212.5 25256.51 25209.77 25207.68 25245.21 25130.97
30 5188409.83 5188250.86 5188885.18 5188999.83 5189365.09 5190159.72 5189771.1 5190136.3 5191179.72 5191256.35 5191147.97 5191712.32
31 1455227.93 1455734.55 1455846 1455774.16 1456130.24 1456289.94 1455711.1 1456447.68 1456588.78 1456796.61 1456867.04 1457081.75
32 192081.97 192166.45 192157.38 192121.78 192203.97 192215.73 192098.89 192181.45 192211.12 192234.93 192245.5 192282.35
33 156346.02 156453.62 156442.94 156392.71 156436.89 156449.56 156363.24 156443.5 156448.72 156429.21 156479.57 156498
34 98025.54 98091.08 98101.41 98052.04 98079.79 98094.76 98012.52 98088.28 98083.11 98091.65 98097.78 98111.77
35
36 3591.13 3619.1 3581.45 3597.28 3610.98 3627.1 3641.58 3639.8 3628.65 3655.72 3649.4 3648.33
37 2915134.44 2916170.14 2916194.3 2916438.93 2916841.46 2916923.27 2916298.61 2916843.73 2917128.84 2916505.26 2917823.72 2917249.33
38 226998.07 227155.45 227099.14 227256.82 227092.64 227274.71 227046.17 227211.35 227271.17 227113.9 227296.57 227410.79
39 25246.49 25073.61 25141.74 25191.55 25275.35 25218.04 25234.66 25144.64 25294.39 25197.99 25252.66 25029.12
40 5192430.88 5193407.95 5192603.89 5192248.7 5192197.65 5193096.79 5193005.25 5193985.8 5193451.22 5193489.16 5193562.72 5194621.43
41 1457274.68 1457155.16 1457782.73 1457065.11 1457459.15 1457347.08 1457837.54 1457999.87 1458171.82 1458241.76 1458320.08 1458622.22
42 192290.05 192278.03 192370.19 192250.39 192308.68 192264.65 192339.55 192365.62 192394.12 192385.72 192403.42 192431.52
43 156535.45 156528.7 156603.81 156486.44 156524.97 156482.7 156558.25 156574.41 156585.45 156572.05 156610.77 156638.11
44 98133.52 98135.26 98181.02 98130.98 98142.39 98103.2 98151.5 98163.1 98181.58 98161.11 98181.91 98207.14
45
46 3676.89 3661.96 3697.21 3689.05 3693.71 3710.29 3734.39 3732.68 3732.57 3760.45 3753.94 3778.77
47 2918275.17 2918657.92 2918593.87 2918092.17 2916450.26 2917383.96 2917260.84 2918251.2 2916669.62 2917421.6 2916740.6 2917259.97
48 227169.76 227314.2 227496.21 227252.71 227267.55 227308.58 227361.06 227333.64 227178.12 227358.18 227154.37 227278.39
49 25239.01 25241.82 25299.99 25249.92 25112.44 25140.67 25247.73 25235.76 25316.81 25188.8 25122.93 25186.04
50 5194170.84 5194198.19 5194866.16 5194030.81 5194421.67 5193745.31 5195458.37 5196342.62 5194881.29 5195036.46 5193627.87 5194470.9
51 1458574.79 1458586.67 1458701.91 1458749.17 1458869.01 1458755.66 1458885 1459167.12 1458881.12 1459110.4 1458918 1459297.49
52 192408.2 192414.77 192419.74 192424.98 192432.85 192422.79 192444.94 192454.58 192456.89 192449 192451.98 192507.83
53 156607.3 156600.19 156626.51 156605.06 156637.24 156611.04 156625.38 156635.17 156644.67 156634.81 156635.81 156690.93
54 98176.71 98194 98203.63 98178.89 98213.34 98179.43 98188.91 98209 98224.92 98202.98 98199.12 98239.48
55
56 3792.45 3764.17 3804.36 3804.46 3807.49 3817.46 3854.72 3820.18 3844.23 3844.19 3856.38 3856.53
57 2916818.62 2917508.43 2918006.44 2917757.21 2918060.88 2915855.65 2918151.83 2917179.65 2918271.42 2917682.08 2916528.9 2916751.82
58 227226.46 227220.65 227276.21 227336.72 227239.63 227201.77 227298.1 227286.38 227398.71 227336.91 227365.81 227255.2
59 25149.75 25127.59 25175.98 25093.1 25224.16 25166.84 25170.27 25203.5 25258.65 25192.54 25154.19 25180.35
60 5195017.44 5194402.87 5194659.24 5194751.51 5195016.87 5194802.11 5195467.68 5194654.04 5195622.23 5194709.45 5195050.77 5195097.58
61 1459375.28 1459338.09 1459413.22 1459726.96 1459926.75 1459943.81 1460193.37 1460242.02 1460274.7 1460319.25 1460494.5 1460347.8
62 192490.77 192504.55 192520.85 192539.33 192549.03 192578.96 192618.21 192638.83 192629.15 192617.57 192651.62 192626.81
63 156666.67 156700.49 156702.44 156705.8 156723.19 156746.24 156784.77 156783.37 156816.63 156767.56 156820.49 156805.69
64 98228.15 98251.45 98263.44 98253.43 98253.53 98293.22 98310.56 98299.46 98324.44 98304.57 98320.92 98331.45
65
66 3856.95 3905.39 3868.66 3898.41 3908.94 3905.1 3942.19 3941.65 3957.9 3936.05 3953.8 3952.5
67 2916524.81 2916802.18 2915576.36 2916073.58 2916285.37 2915885.03 2916843.4 2916897 2916226.64 2916329.2 2915110.13 2914458.88
68 227241.09 227129.99 227074.28 227152.61 227331.13 227349.15 227404.26 227317.63 227228.69 227163.85 226953.01 226922.52
69 25197.78 25340.6 25224.43 25173.91 25205.17 25253.24 25325.32 25459.4 25186.6 25238.33 25237.85 25130.99
70 5195987.22 5195831.3 5194776.48 5193605.12 5194317.87 5194089.21 5194563.64 5193895.14 5194140.95 5193791.85 5193915.21 5194343.34
71 1460589.02 1460436.82 1460754.06 1460643.79 1460803.29 1460817.97 1460948.1 1460903.97 1460944.45 1460874.04 1460929.33 1461072.84
72 192649.6 192636.68 192703.22 192661.42 192687.33 192704.48 192729.77 192731.6 192742.22 192701.82 192729.55 192743.99
73 156799.75 156813.77 156847.63 156837.49 156841.06 156833.21 156873.62 156877.83 156877.8 156836.4 156876.97 156889.26
74 98315.52 98316.35 98350.96 98356.69 98336.74 98322.17 98356.82 98367.58 98355.18 98342.84 98346.7 98374.95
75
76 3986.09 3972.33 3974.86 3962.69 4006.6 4007.01 4013.11 4036.94 3981.75 3982.69 3982.16 4017.66
77 2916433.5 2915075.24 2915229.63 2913743.19 2914563.32 2913637.85 2914569.65 2914736.45 2913404.01 2913008.04 2913627.33 2914075.7
78 227207.38 227141.31 227117.31 227162.19 227210.19 227078.05 227066.16 227226.41 226951.75 226963.37 226956.1 227106.71
79 25303.22 25188.74 25226.41 25190.27 25082.58 25059.87 25295.12 25197.11 25222.02 25208.2 25173.89 25197.88
This is my problem. I want the dataframes in line and stacked on top of each other.
解决方案
You're very nearly there.
The problem is that the column names are all different within each sub dataframe. Thus, when pandas does the concat, it doesn't just append the dataframes to the bottom, it expands the dataframe to have new colums with the right names and then appends the rows.
You can solve this by renaming the columns in the sub dataframes e.g.
for sub_df in pieces:
sub_df.columns=range(12)
N.B. df2 to df8 contain what you want, I think. For some reason, you've made df1 contain only the first 7 columns, rather than 12. I'll assume that's a typo for now.
Resulting in full working code (I copied your input data into a file named 'data1.csv')
import pandas as pd
import numpy as np
df = pd.read_csv('data1.csv')
df1 = df.ix[:,0:12]
df2 = df.ix[:,12:24]
df3 = df.ix[:,24:36]
df4 = df.ix[:,36:48]
df5 = df.ix[:,48:60]
df6 = df.ix[:,60:72]
df7 = df.ix[:,72:84]
df8 = df.ix[:,84:96]
pieces = (df1,df2,df3,df4,df5,df6,df7,df8)
# Give the columns the same labels in each sub dataframe
# I've used numbers for convenience - you can give more descriptive names if you want
for sub_df in pieces:
sub_df.columns=range(12)
df_final = pd.concat(pieces, ignore_index = True)
print df_final
Final note on ordering
You note the unexpected ordering of your columns in your example. This won't affect my solution, but I will explain it for completeness.
The columns in your output are in what is called 'Lexicographic ordering'. This is a common problem when sorting strings containing numbers in Python (and other languages). They are sorted in an order that looks almost right, but somehow runs 1, 10, 11 ... 19, 2, 20 and so on. That is because the ordering sorts letter by letter like a dictionary, but with 0 to 9 coming before a
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