I need to analyze data with Python. I created a csv file in excel before. But when I show the table with python, only one column seems to have all numbers in decimals. Excel also looks fine, but when I show it in python it looks decimal. Please help!
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
df = pd.read_csv("covıd.csv" , sep=';', encoding='latin-1')
df
The Total Case part looks decimal. not improving. It wasn't like this before.
Related
I've been pulling my hair out trying to make a bipartite graph from a csv file and so far all I have is a panda matrix that looks like this
My code so far is just
`
import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# import pyexcel as pe
# import pyexcel.ext.xlsx
from networkx.algorithms import bipartite
mat = pd.read_csv("networkdata3.csv")
# mat = pd.read_excel("networkdata1.xlsx",sheet_name="sheet_name_1")
print(mat.info)
sand = nx.from_pandas_adjacency(mat)
`
and I have no clue what I'm doing wrong. Initially I was trying to read it in as the original xlsx file but then I just converted it to a csv and it started reading. I assume I can't make the graph because the column numbers are decimals and the error that spits out claims that the column numbers don't match up. So how else should I be doing this to actually start making some progress?
I am trying to read in some currency data from an excel sheet which has values with 10 decimal places, but when i read it in within the df it is dropping all the values to 2 decimal places which i dont want. Any help on how to get all the decimal places back would be great.
import pandas as pd
import numpy as np
import xlrd as xlrd
import xlsxwriter
df = pd.read_excel('Currency Data.xls','PPU')
df.head()
I would suggest looking at the Decimal library for python
https://docs.python.org/2/library/decimal.html
Before reading into pandas, data is used in sasdataset. My data looks like
SNYDJCM--integer
740.19999981
After reading into pandas my data is changing as below
SNYDJCM--converting to float
740.200000
How to get same value after reading into pandas dataframe
Steps followed:
1)
import pandas as pd
2)
pd.read_sas(path,format='sas7bdat',encoding='iso-8859-1')
Need your help
Try import SAS7BDAT and casting your file before reading:
from sas7bdat import SAS7BDAT
SAS7BDAT('FILENAME.sas7bdat')
df = pd.read_sas('FILENAME.sas7bdat',format='sas7bdat')
or use it to directly read the file:
from sas7bdat import SAS7BDAT
sas_file = SAS7BDAT('FILENAME.sas7bdat')
df = sas_file.to_data_frame()
or use pyreadstat to read the file:
import pyreadstat
df, meta = pyreadstat.read_sas7bdat('FILENAME.sas7bdat')
First 740.19999981 is no integer 740 would be the nearest integer. But also when you round 740.19999981 down to 6 digits you will get 740.200000. I would sugest printing out with higher precision and see if it is really changed.
print("%.12f"%(x,))
I've exported an Excel into a CSV where all the columns and entires look correct and normal. However, when I put it into a data frame and print the head, the structure becomes very messy and unreadable due to columns being unstructured.
As you can see in the image, the values are not neatly under user_id.
https://imgur.com/a/gbWaTwi
I'm using the following code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import warnings
warnings.filterwarnings("ignore")
then
df1 = pd.read_csv('../doc.csv', low_memory=False)
df1.head
Do this --- print the invocation of head. Just saying .head isn't enough.
print(df1.head())
I am trying to load data from the web source and save it as a Excel file but not sure how to do it. What should I do? The original dataframe has different columns. Let's say that I am trying to save 'Open' column
import matplotlib.pyplot as plt
import pandas_datareader.data as web
import datetime
import pandas as pd
def ViewStockTrend(compcode):
start = datetime.datetime(2015,2,2)
end = datetime.datetime(2016,7,13)
stock = web.DataReader(compcode,'yahoo',start,end)
print(stock['Open'])
compcode = ['FDX','GOOGL','FB']
aa= ViewStockTrend(compcode)
Once you have made the pandas dataframe just use to_excel on the entire thing if you want:
aa.to_excel('output/filename.xlsx')
If stock is a pandas DataFrame, you need to construct a new Framefrom that column and output that one to excel:
df = pd.DataFrame(stock['Open'])
df.to_excel('path/to/your/file')