I could import excel data into python 3.6 using pandas.
Code I used for this purpose is as follows:
import pandas as pd
import numpy as np
df=pd.read_excel("I:/Python/Excel.xlsx")
df.head()
This above code shows me the Table1 on Jupyter notebook.
I am not getting how to convert two columns from the Table1 (obtained from above code) which I can see in Jupyter notebook to numpy arrays inorder to carry out further analysis on them.
There are in all 17 columns in this table. I need 'Column 15' and 'Column 16' from pandas frame work into numpy array so that final structure is as follows:
data_set=[[x1,y1],[x2,y2],...[x1000,y1000]]
# x1 = row1 from Column 15
# y1 = row1 from Column 16
I will be finally using this data to plot 'xy scatter plot' into matplotlib. This part I know how to do. Learned a lot from this forum. Thanks to all!
I looked online for this solution, but unable to find a solution for it.
Thanks for reading.
I think need select columns by positions by iloc, convert to numpy array and if neccesary to list:
np.random.seed(1245)
df = pd.DataFrame(np.random.randint(10, size=(3, 17))).add_prefix('data')
print (df)
data0 data1 data2 data3 data4 data5 data6 data7 data8 data9 \
0 6 5 3 5 0 6 9 3 4 6
1 7 1 2 9 3 9 8 8 7 1
2 4 1 8 2 5 6 6 5 1 5
data10 data11 data12 data13 data14 data15 data16
0 9 4 9 5 2 7 9
1 7 5 5 2 2 4 0
2 4 6 6 0 2 7 6
data_set = df.iloc[:, [14, 15]].values.tolist()
#alternative
#data_set = df.values[:, [14, 15]].tolist()
print(data_set)
[[2, 7], [2, 4], [2, 7]]
EDIT:
#if want select columns by names
x = df['data01']
y = df['data02']
#if want select columns by positions
#x = df.iloc[:, 1]
#y = df.iloc[:, 2]
s = plt.scatter(x, y)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With