CODEWITHSUNDEEP
pythonpandasdataframematplotlibappend
user9410826
user9410826

Reputation:

Append multiple columns from a df into a list

I am trying to import xy coordinates from multiple columns into a list. I can get it going when the coordinates are read from a single column but struggling to get it to read from multiple columns efficiently.

I need this for plotting

Attempt:

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

d = ({
    'Time' : [1,2,3,4,5,6,7,8],       
    'GrA1_X' : [10,12,17,16,16,14,12,8],                 
    'GrA1_Y' : [10,12,13,7,6,7,8,8], 
    'GrA2_X' : [5,8,13,16,19,15,13,5],                 
    'GrA2_Y' : [6,15,12,7,8,9,10,8],
    'GrB1_X' : [15,18,25,16,6,15,17,10],                 
    'GrB1_Y' : [7,12,5,9,10,12,18,9], 
    'GrB2_X' : [10,4,18,14,16,12,17,4],                 
    'GrB2_Y' : [8,12,16,8,10,14,12,15],         
     })

df = pd.DataFrame(data=d)

GrA_X = df[df.columns[1::2][:2]]
GrA_Y = df[df.columns[2::2][:2]]

GrB_X = df[df.columns[5::2][:2]]
GrB_Y = df[df.columns[6::2][:2]]

fig = plt.figure(figsize=(10,6))
ax = plt.gca()

Zs = []
for l,color in zip('AB', ('red', 'blue')):
    # plot all of the points from a single group
    ax.plot(GrA_X.iloc[0], GrA_Y.iloc[0], '.', c='red', ms=15, label=l, alpha = 0.5)
    ax.plot(GrB_X.iloc[0], GrB_Y.iloc[0], '.', c='blue', ms=15, label=l, alpha = 0.5)    

    Zrows = []
    for _,row in df.iterrows():
        x,y = row['Gr%s_X'%l], row['Gr%s_Y'%l]

I'm stuck with the Zrows = [] call. Specifically, how to append multiple columns within this list.

Upvotes: 1

Views: 2808

Answers (2)

griggy
griggy

Reputation: 446

This could be an alternative solution, given I am understanding your problem correctly.

df = pd.DataFrame(data=d)
X = [df[c].tolist() for c in df.columns if c.find("_X") >= 0]
Y = [df[c].tolist() for c in df.columns if c.find("_Y") >= 0]

allX = [x for sublist in X for x in sublist]
allY = [y for sublist in Y for y in sublist]

dfXY = pd.DataFrame({"X": allX, "Y":allY})

Now you have all x's and y's in a simple dataframe. Cheers

Upvotes: 1

Thomas Kühn
Thomas Kühn

Reputation: 9810

I'm still not clear whether I understand the purpose of the last loop correctly, but I'll take the risk and suggest a solution. Your problem seems to be with the naming of the columns and I don't see another way except looping over the different variations of Gr{A,B}{1,2}_{X,Y} (here the {} indicate variations). I would go with a nested for-loop, i.e.:

Zs = []
for l,color in zip('AB', ('red', 'blue')):
    # plot all of the points from a single group
    ax.plot(GrA_X.iloc[0], GrA_Y.iloc[0], '.', c='red', ms=15, label=l, alpha = 0.5)
    ax.plot(GrB_X.iloc[0], GrB_Y.iloc[0], '.', c='blue', ms=15, label=l, alpha = 0.5)    

    Zrows = []
    for _,row in df.iterrows():
        for i in [1,2]:
            x,y = row['Gr{}{}_X'.format(l,i)], row['Gr{}{}_Y'.format(l,i)]
            Zrows.append((x,y))


print(Zrows)

which gives a list of coordinate tuples:

[(15, 7), (10, 8), (18, 12), (4, 12), (25, 5), (18, 16), (16, 9), (14, 8), (6, 10), (16, 10), (15, 12), (12, 14), (17, 18), (17, 12), (10, 9), (4, 15)]

Note that I changed the string formatting to the format()-syntax, which in my opinion vastly increases readability. Please let me know if this is even close to what you are after.

Upvotes: 0

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