convert one row/n-columns to multi-rows/3-columns python-pandas

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I am trying to convert a single row multiple columns (.csv) to n-rowsx3columns and save it in a new file (csv or txt)



I want:



import pandas as pd
df=pd.read_csv('~\datatest\datatest2.csv', sep=',')
for i in len (0, len(df), 3):
df1.to_csv('~\datatest\out.csv', sep=',')
with open('~\datatest\datatest2.csv', 'r') as f:
    v = f.readline().split(',')

with open('~\datatest\out.csv', 'w') as f:
    for n in range(len(v)//3):
        f.write(','.join(v[n*3:(n+1)*3]) + '\n')

convert one row/n-columns to multi-rows/3-columns python-pandas, I am trying to convert a single row multiple columns (.csv) to n-rowsx3columns and save it in a new file (csv or txt). Data: 51.9596,-115.1437,6.0000,51.9596  Convert column to row in Python Pandas. Ask Question Asked 3 years, 4 months ago. Active 7 months ago. Viewed 58k times 25. 8. I have the following Python pandas

By what I understood, this should do the trick:

import pandas as pd
df=pd.read_csv('~\datatest\datatest2.csv', sep=',')

#reshaping your dataframe as an array and storing it in df2
df2 = df.values.reshape(int(len(df.columns)/3), 3)

#converting df2 (that's currently an array) to a dataframe
df2 = pd.DataFrame.from_records(df2)

#exporting it
df2.to_csv(your_filepath, separator)

Selecting Multiple Rows and Columns, .loc .iloc .ix. In [1]:. import pandas as pd. In [3]:. url = '' ufo rows and selecting columns by label # format # ufo.loc[rows, columns] # row 0,  OLD(ER) VERSIONS: <0.20. You can use pd.melt to get most of the way there, and then sort: >>> df location name Jan-2010 Feb-2010 March-2010 0 A test 12 20 30 1 B foo 18 20 25 >>> df2 = pd.melt(df, id_vars=["location", "name"], var_name="Date", value_name="Value") >>> df2 location name Date Value 0 A test Jan-2010 12 1 B foo Jan-2010 18 2 A test Feb-2010 20 3 B foo Feb-2010 20 4 A test March

linelist = '''51.9596,-115.1437,6.0000,51.9596,-115.1285,6.0000,51.9686,-115.1588,6.0000,51.9686,-115.1437,10.5000,51.9686,-115.1285,10.5000,51.9686,-115.1134,8.0000,51.9776,-115.1891,7.5000,51.9776,-115.1740,7.5000,51.9776,-115.1588,7.5000,51.9776,-115.1437,8.0000,51.9776,-115.1285,8.0000,51.9776,-115.1134,8.0000,51.9866,-115.1891,7.0000'''
linelist = linelist.split(',')

col1 = [float(x)%1 for x in linelist]
col2 = [float(x)%2 for x in linelist]
col3 = [float(x)%3 for x in linelist]
datadict = {'col1':col1, 'col2':col2, 'col3':col3}
import pandas as pd
df = pd.DataFrame(datadict)

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Reshaping and pivot tables, N = 3 def unpivot(frame): N, K = frame.shape data = {'value': In [3]: df.pivot(​index='date', columns='variable', values='value') Out[3]: variable and the input DataFrame has more than one column of values which are not used as column hierarchical) row index to the column axis, producing a reshaped DataFrame with a  Accessing pandas dataframe columns, rows, and cells At this point you know how to load CSV data in Python. In this lesson, you will learn how to access rows, columns, cells, and subsets of rows and columns from a pandas dataframe.

pandas.DataFrame, Changed in version 0.23.0: If data is a dict, argument order is maintained for Python 3.6 and later. index : Index or array- Will default to RangeIndex (0, 1, 2, …, n) if no column labels are provided DataFrame(data=d) >>> df col1 col2 0 1 3 1 2 4. Notice that Convert structured or record ndarray to DataFrame. ge (​other[  How to select multiple columns in a pandas dataframe Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

  • Thanks @helena-martins, but i received this error for the "df=2df.values.reshape" line CANNOT RESHAPE ARRAY OF SIZE 0 INTO SHAPE (63277,3)
  • There is a syntax error. It should be df2 = df.values.reshape. Try moving the 2 to the other side of the equation
  • the error is for this line "df2 = df.values.reshape(int(len(df.columns)/3), 3)" CANNOT RESHAPE ARRAY OF SIZE 0 INTO SHAPE (63277,3)
  • According to the error, and considering you did exactly what I specified, your dataframe is most probably empty. Could you show the entire code, exactly the way it is now?
  • import pandas as pd df = pd.read_csv('H:/datatest/datatest2.csv', sep=',') df2 = df.values.reshape(int(len(df.columns)/3), 3) f2 = pd.DataFrame.from_records(df2) df2.to_csv('H:/datatest/datatest2out.csv', sep=',')