我有一个数据框，我想将该数据框划分为等宽的条带（每个条带中的数据点数可能不相同）。我尝试了以下方法
df = pc13.sort_values(by = ['A'], ascending=True)
df_temp = np.array_split(df, 20)
但是这种方法是将数据帧分为具有相同数量数据点的bin。取而代之的是，我想将数据帧划分为特定宽度的bin，每个bin中数据点的数量也可能不相同。
数据帧列A中的最小值是-0.04843731030699292，最大值是0.05417013917000033。我尝试上传整个数据框，但这是一个很大的文件。
答案 0 :(得分：1)
您可以执行以下操作：
# create a random df
df = pd.DataFrame(np.random.randn(10, 10), columns=list('ABCDEFGHIJ'))
# sort valeus
df = df.sort_values(by = ['A'], ascending=True)
# use your code but on a transposed dataframe
new = np.array_split(df.T, 5) # split columns into 5 bins
# list comprehension to transposed dataframes
dfs = [new[i].T for i in range(len(new))]
# random df
df = pd.DataFrame(np.random.randn(1000, 5), columns=list('ABCDE'))
# sort on A
df.sort_values('A', inplace=True)
# create bins
df['bin'] = pd.cut(df['A'], 20, include_lowest = True)
# group on bin
group = df.groupby('bin')
# list comprehension to split groups into list of dataframes
dfs = [group.get_group(x) for x in group.groups]
[ A B C D E bin
218 -2.716093 0.833726 -0.771400 0.691251 0.162448 (-2.723, -2.413]
207 -2.581388 -2.318333 -0.001467 0.035277 1.219666 (-2.723, -2.413]
380 -2.499710 1.946709 -0.519070 1.653383 0.309689 (-2.723, -2.413]
866 -2.492050 0.246500 -0.596392 0.872888 2.371652 (-2.723, -2.413]
876 -2.469238 -0.156470 -0.841065 -1.248793 -0.489665 (-2.723, -2.413]
314 -2.456308 0.630691 -0.072146 1.139697 0.663674 (-2.723, -2.413]
310 -2.455353 0.075842 0.589515 -0.427233 1.207979 (-2.723, -2.413]
660 -2.427255 0.890125 -0.042716 -1.038401 0.651324 (-2.723, -2.413],
A B C D E bin
571 -2.355430 0.383794 -1.266575 -1.214833 -0.862611 (-2.413, -2.11]
977 -2.354416 -1.964189 0.440376 0.028032 -0.181360 (-2.413, -2.11]
83 -2.276908 0.288462 0.370555 -0.546359 -2.033892 (-2.413, -2.11]
196 -2.213729 -1.087783 -0.592884 1.233886 1.051164 (-2.413, -2.11]
227 -2.146631 0.365183 -0.095293 -0.882414 0.385117 (-2.413, -2.11]
39 -2.136800 -1.150065 0.180182 -0.424071 0.040370 (-2.413, -2.11],
A B C D E bin
104 -2.108961 -0.396602 -1.014224 -1.277124 0.001030 (-2.11, -1.806]
360 -2.098928 1.093483 1.438421 -0.980215 0.010359 (-2.11, -1.806]
530 -2.088592 1.043201 -0.522468 0.482176 -0.680166 (-2.11, -1.806]
158 -2.062759 2.070387 2.124621 -2.751532 0.674055 (-2.11, -1.806]
971 -2.053039 0.347577 -0.498513 1.917305 -1.746493 (-2.11, -1.806]
658 -2.002482 -1.222292 -0.398816 0.279228 -1.485782 (-2.11, -1.806]
90 -1.985261 3.499251 -2.089028 1.238524 -1.781089 (-2.11, -1.806]
466 -1.973640 -1.609920 -1.029454 0.809143 -0.228893 (-2.11, -1.806]
40 -1.966016 -1.479240 -1.564966 -0.310133 1.338023 (-2.11, -1.806]
279 -1.943666 0.762493 0.060038 0.449159 0.244411 (-2.11, -1.806]
204 -1.940045 0.844901 -0.343691 -1.144836 1.385915 (-2.11, -1.806]
780 -1.918548 0.212452 0.225789 0.216110 1.710532 (-2.11, -1.806]
289 -1.897438 0.847664 0.689778 -0.454152 -0.747836 (-2.11, -1.806]
159 -1.848425 0.477726 0.391384 -0.477804 0.168160 (-2.11, -1.806],
. . .