How could I transform the numpy array to pandas dataframe?

Question

I am new to analyze using python, I wonder how can I transform the format of the left table to the right one. My initial thought is to create a nested for loop.

The desired table First, I find read the required csv file.

Imported csv

Then, I count the number of countries in the Column 'country' and the number of the new column names list.

`countries = len(test['country'])`
`columns = len(['Year', 'Values'])`

After that, I should go for the nested for loop, however, I have no idea on writing the code.What I have come up was as follows:

`for i in countries:`
  `for j in columns:`

Mayank Porwal · Accepted Answer · 2020-11-25 18:39:01Z

2

You can use df.melt here:

In [3575]: df = pd.DataFrame({'country':['Afghanistan', 'Albania'], '1970':[1.36, 6.1], '1971':[1.39, 6.22], '1972':[1.43, 6.34]})

In [3576]: df
Out[3576]: 
       country  1970  1971  1972
0  Afghanistan  1.36  1.39  1.43
1      Albania  6.10  6.22  6.34

In [3609]: df = df.melt('country', var_name='Year', value_name='Values').sort_values('country')

In [3610]: df
Out[3610]: 
       country  Year  Values
0  Afghanistan  1970    1.36
2  Afghanistan  1971    1.39
4  Afghanistan  1972    1.43
1      Albania  1970    6.10
3      Albania  1971    6.22
5      Albania  1972    6.34

edited Nov 25, 2020 at 18:39

answered Nov 25, 2020 at 15:47

Mayank Porwal

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5 Comments

Mayank Porwal Over a year ago

@CheTou Please check my answer. Let me know if this is what you want.

dallonsi Over a year ago

not sure that this is what he wanted: i.sstatic.net/lH1hq.png

Mayank Porwal Over a year ago

@dallonsi My output matches exactly the output pasted by OP in the image. What am I missing here?

dallonsi Over a year ago

oh right my mistake ! He starts with this table : i.sstatic.net/aOMu7.png I thought he wanted to go from the right table to the left table on this image i.sstatic.net/lH1hq.png .... !!

Crazy Over a year ago

@Mayank Porwal Yes, this is what I want. And I have asked my friend the same question and he gave me another approach to get the same result

dallonsi · Accepted Answer · 2020-11-25 21:06:59Z

0

Not sure of what you want to do, but:

If you want to transform a column in a numpy array, you can use the following example:

import pandas as pd
import numpy as np

df = pd.DataFrame({"foo": [1,2,3], "bar": [10,20,30]})
print(df)

foo_array = np.array(df["foo"])
print(foo_array)

and then iterate on foo_array

You can also loop on your data frame using :

for row in df.iterrows():
    print(row)

But it's not recommended since you can often use built in pandas function to do the same job.

your data frame is also an iterable object which only contains the columns names:

for d in df:
    print(d)

# output:
# foo
# bar

edited Nov 25, 2020 at 21:06

answered Nov 25, 2020 at 15:01

dallonsi

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1 Comment

Crazy Over a year ago

I would like to change the columns' name in the original table to values in the new columns, just like this image, i.sstatic.net/lH1hq.png

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