javascript - pandas df into nested json -
quite similar question asked there, , brilliantly answered user1609452 in r. still, specific problematic. i'd expand question. let's take same table (mydata):
id location l_size l_color station s_size s_color category c_size c_color 1 alpha 6 #000000 zeta 3 #333333 big 0.63 #306100 2 alpha 6 #000000 zeta 3 #333333 medium 0.43 #458b00 3 alpha 6 #000000 zeta 3 #333333 small 0.47 #6aa232 4 alpha 6 #000000 yota 3 #4c4c4c big 0.85 #306100 5 alpha 6 #000000 yota 3 #4c4c4c medium 0.19 #458b00 6 alpha 6 #000000 yota 3 #4c4c4c small 0.89 #6aa232 7 beta 6 #191919 theta 4 #666666 big 0.09 #306100 8 beta 6 #191919 theta 4 #666666 medium 0.33 #458b00 9 beta 6 #191919 theta 4 #666666 small 0.79 #6aa232 10 beta 6 #191919 theta 4 #666666 big 0.89 #306100 11 beta 6 #191919 meta 3 #7f7f7f medium 0.71 #458b00 12 beta 6 #191919 meta 3 #7f7f7f small 0.59 #6aa232 each category has 1 or multiple attributes (here, one: size). i'd like, it's report size each parent/children in json file:
{ "name":"mydata", "size":12, "color":"#ffffff" "children":[ { "name":"alpha", "size":6, "color":"#000000" "children":[ { "name":"zeta", "size":3, "color":"#333333" "children":[ { "name":"big", "size":0.63, "color":"#306100" }, ... etc. couldn't make in r, nor in pandas... idea?
edit: goal link diverse information children, not size. added color column each main column. initial dataframe big , has lot of information, can't paste here, clarity sake.
second edit: chrisb answer worked! great update. still json file isn't uploaded javascript file. file seems upside down (mydata @ end), , information parent before , after children information:
{ "children":[ { "color":"#000000", "children":[ { "color":"#4c4c4c", "children":{ "color":"#306100", "name":"big", "size":0.85 }, "name":"yota", "size":3 }, { "color":"#333333", "children":{ "color":"#306100", "name":"big", "size":0.63 }, "name":"zeta", "size":3 } ], "name":"alpha", "size":6 }, { "color":"#191919", "children":[ { "color":"#7f7f7f", "children":{ "color":"#458b00", "name":"medium", "size":0.71 }, "name":"meta", "size":3 }, { "color":"#666666", "children":{ "color":"#306100", "name":"big", "size":0.09 }, "name":"theta", "size":4 } ], "name":"beta", "size":6 } ], "name":"mydata", "size":12 last edit: works fine. chris removed last part of script wrote when updated it, here is. chris!
data = {'name': 'mydata', 'size': len(mydata), 'children': make_children(mydata, levels)} print json.dumps(data)
first, need kind of mapping of makes each level. i'm using tuples of column defines "name" , prefix of other attributes want level, this.
levels = [('location', 'l_'), ('station', 's_'), ('category', 'c_')] then, it's similar recursive function, columns being picked @ each step (finding columns start prefix) , being added tree zipping the columns / values. there's room clean up, should @ least give idea.
def make_children(df, levels): if len(levels) == 1: name, prefix = levels[0] level_cols = [name] + [c c in df if c.startswith(prefix)] df = df[level_cols] key_names = ['name'] + [c.strip(prefix) c in level_cols[1:]] return dict(zip(key_names, df.values[0])) else: h, tail = levels[0], levels[1:] name, prefix = h level_cols = [name] + [c c in df if c.startswith(prefix)] data = [] keys, df_gb in df.groupby(level_cols): key_names = ['name'] + [c.strip(prefix) c in level_cols[1:]] d = dict(zip(key_names, keys)) d['children'] = make_children(df_gb, tail) data.append(d) return data
Comments
Post a Comment