This question already has answers here:
Pandas: Setting no. of max rows
(10 answers)
Closed 1 year ago.
I am working with python 3 and the pandas package in visual studio code and I the print() function is not displaying correctly.
For example when I am using df.head() it looks good.
But If I use the print() statement I no longer see all of the columns next to each other, some of them get dragged down for some reason. And I can't see the entire data
Anyone knows what I can do to see the entire data, and all of the columns next to each other?
The problem comes from library pandas that cuts part of your dataframe when it's too long. Before your print, add this line:
pandas.set_option('max_row', None)
to display the entier row.
Also, you will be able to see all your data adding None argument in head():
trading.head(None)
Related
I figured out how to sort the data from most recent to least recent, but I'm having trouble figuring out a command to show a specific time frame. The years I'm looking for are 2016-2008. I included the data frame that needs to be filtered in the link.
It's my first time posting a picture, so it's only allowing me to post as it link. I hope it's visible.
I take it this is a pandas dataframe?
it should just be:
rows = data[(data.years >= 2008) & (data.years <= 2016)]
where the dataframe is called 'data' and years is the row.
Try this
rows = all_rows[(all_rows['Year']>=2008) and (all_rows['Year']<=2016)]
This question already has answers here:
Change the number of lines shown in Visual Studio Code's built-in Terminal
(3 answers)
Closed 2 years ago.
I want to inspect all unique values in a column in a pandas dataframe, however, using df.column.unique() only gives the starting and ending values, and values in the middle are hidden with an ellipsis.
I tried
mylist = list(df.column.unique())
mylist
which showed more values but not till the end.
Edit:
mylist ouput looks like this:
['PSPC000',
'LEV12345RTC',
'LV150390XYZ',
'WPX-100',
'FSM-Y2222',
'FM-YX3',
'ELB1100',
'Lx145BP',
'CE503pxp',
'Exxy351',
...]
Try this:
print (df.column.unique().tolist())
This question already has answers here:
How can I display full (non-truncated) dataframe information in HTML when converting from Pandas dataframe to HTML?
(10 answers)
Closed 3 years ago.
I want to show content of a dataframe that I created. The problem is that it shows only part of the column content:
Is there an option to see all the columns' content?
You can try using dataframe.head(n=100). Just change the value of n to how many items you want to display
This question already has answers here:
Deleting multiple columns based on column names in Pandas
(11 answers)
Closed 4 years ago.
I can't figure this bug out. I think it is my misunderstanding of a dataframe and indexing through one. Also, maybe a misunderstanding of a for loop. (I am used to matlab for loops... iterations are, intuitively, way easier :D)
Here is the error:
KeyError: "['United States' 'Canada' 'Mexico'] not found in axis"
This happens at the line: as_df=as_df.drop(as_df[column])
But this makes no sense... I am calling an individual column not the entire set of dummy variables.
The following code can be copied and ran. I made sure of it.
MY CODE:
import pandas as pd
import numpy as np
df=pd.DataFrame({"country": ['United States','Canada','Mexico'], "price": [23,32,21], "points": [3,4,4.5]})
df=df[['country','price','points']]
df2=df[['country']]
features=df2.columns
print(features)
target='points'
#------_-__-___---____________________
as_df=pd.concat([df[features],df[target]],axis=1)
#Now for Column Check
for column in as_df[features]:
col=as_df[[column]]
#Categorical Data Conversion
#This will split the countries into their own column with 1 being when it
#is true and 0 being when it is false
col.select_dtypes(include='object')
dummies=pd.get_dummies(col)
#ML Check:
dumcols=dummies.drop(dummies.columns[1],axis=1)
if dumcols.shape[1] > 1:
print(column)
as_df=as_df.drop(as_df[column])
else:
dummydf=col
as_df=pd.concat([as_df,dummydf],axis=1)
as_df.head()
I would comment instead of answering, but I do not have enough reputation to do so. (I need clarification to help you and Stack Exchange does not provide me with a way to do so "properly".)
I'm not entirely sure what your end-goal is. Could you clarify what your end result for as_df would look like? Including after the for loop ends, and after the entire code is finished running?
Found my mistake.
as_df=as_df.drop(as_df[column])
should be
as_df=as_df.drop(column,axis=1)
This question already has answers here:
How to deal with SettingWithCopyWarning in Pandas
(20 answers)
Closed 4 years ago.
I have a small dataframe, say this one :
Mass32 Mass44
12 0.576703 0.496159
13 0.576658 0.495832
14 0.576703 0.495398
15 0.576587 0.494786
16 0.576616 0.494473
...
I would like to have a rolling mean of column Mass32, so I do this:
x['Mass32s'] = pandas.rolling_mean(x.Mass32, 5).shift(-2)
It works as in I have a new column named Mass32s which contains what I expect it to contain but I also get the warning message:
A value is trying to be set on a copy of a slice from a DataFrame. Try
using .loc[row_indexer,col_indexer] = value instead
See the the caveats in the documentation:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
I'm wondering if there's a better way to do it, notably to avoid getting this warning message.
This warning comes because your dataframe x is a copy of a slice. This is not easy to know why, but it has something to do with how you have come to the current state of it.
You can either create a proper dataframe out of x by doing
x = x.copy()
This will remove the warning, but it is not the proper way
You should be using the DataFrame.loc method, as the warning suggests, like this:
x.loc[:,'Mass32s'] = pandas.rolling_mean(x.Mass32, 5).shift(-2)