CODEWITHSUNDEEP
pythonpandas
GeoMonkey
GeoMonkey

Reputation: 1671

Pandas ValueError: Shape of passed values

In the following code I iterate through a list of images and count the frequencies of a given number, in this case zeros and ones. I then write this out to a csv. This works fine when I write out the list of frequencies only, but when I try to add the filename then I get the error: 

ValueError: Shape of passed values is (1, 2), indices imply (2, 2)

When I try to write out one list of frequencies (number of ones) and the filenames it works fine.

My code is as follows:

import os
from osgeo import gdal
import pandas as pd
import numpy as np

# Input directory to the .kea files
InDir = "inDirectory"

# Make a list of the files
files = [file for file in os.listdir(InDir) if file.endswith('.kea')]

# Create empty list to store the counts
ZeroValues = []
OneValues = []

# Iterate through each kea file and open it
for file in files:
    print('opening ' + file)
    # Open file
    ds = gdal.Open(os.path.join(InDir, file))
    # Specify the image band
    band = ds.GetRasterBand(1)
    # Read the pixel values as an array
    arr = band.ReadAsArray()
    # remove values that are not equal (!=) to 0 (no data)
    ZeroPixels = arr[arr==0]
    OnePixels = arr[arr==1]
    print('Number of 0 pixels = ' + str(len(ZeroPixels)))
    print('Number of 1 pixels = ' + str(len(OnePixels)))
    # Count the number of values in the array (length) and add to the list
    ZeroValues.append(len(ZeroPixels))
    OneValues.append(len(OnePixels))
    # Close file
    ds = Non

# Pandas datagram and out to csv
out = pd.DataFrame(ZeroValues, OneValues, files)
# Write the pandas dataframe to a csv
out.to_csv("out.csv", header=False, index=files)

Upvotes: 1

Views: 1744

Answers (1)

andrew_reece
andrew_reece

Reputation: 21284

Pandas thinks you're trying to pass OneValues and files as positional index and columns arguments. See docs.

Try wrapping your fields in a dict:

import pandas as pd

ZeroValues = [2,3,4]
OneValues = [5,6,7]
files = ["A.kea","B.kea","C.kea"]

df = pd.DataFrame(dict(zero_vals=ZeroValues, one_vals=OneValues, fname=files))

Output:

   fname  one_vals  zero_vals
0  A.kea         5          2
1  B.kea         6          3
2  C.kea         7          4

Upvotes: 2

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