Develop Reference

Reset index and present data in table format

I am using the following code -
import pandas as pd
from mftool import Mftool
import pandas as pd
import os
import time
mf = Mftool()
data =mf.get_scheme_historical_nav('138564',as_Dataframe=True)
data = data.rename_axis("Date",index= False)`
`
The above mentioned code gives me data in the following format -
enter image description here
Clearly, Date has been set to index, but i want to
keep 'Date' column in my df without categorizing it as index.
change dd-mm-yyyy to yyyy-mm-dd
can anybody help, thank you!
I tried using following, but it was not useful -
'data = data.set_index(to_datetime(data['Date']))
'data.d['Date'] = pd.to_datetime(data['Dateyour text'])'`

How to extract data from an api using python and convert it into a pandas data frame

I want to load the data from an API into a pandas data frame. How may I do that? The following is my code snippet:
import requests
import json
response_API = requests.get('https://data.spiceai.io/eth/v0.1/gasfees?period=1d')
#print(response_API.status_code)
data = response_API.text
parse_json = json.loads(data)

Almost there, the json is clean you can directly input it to a dataframe :
response_API = requests.get('https://data.spiceai.io/eth/v0.1/gasfees?period=1d')
data = response_API.json()
df = pd.DataFrame(data)

Filter data from a created list

I am working on my Covid data set from github and I would like to filter my data set with the countries that appear in the this EU_member list in csv format.
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv')
df = df[df.continent == 'Europe']
# From here I want to just pick those countries that appear in the following list:
EU_members= ['Austria','Italy','Belgium''Latvia','Bulgaria','Lithuania','Croatia','Luxembourg','Cyprus','Malta','Czechia','Netherlands','Denmark','Poland','Estonia',
'Portugal','Finland','Romania','France','Slovakia','Germany','Slovenia','Greece','Spain','Hungary','Sweden','Ireland']
# I have tried something like this but it is not what I expected:
df.location.str.find('EU_members')

You can use .isin():
import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/owid-covid-data.csv')
EU_members= ['Austria','Italy','Belgium''Latvia','Bulgaria','Lithuania','Croatia','Luxembourg','Cyprus','Malta','Czechia','Netherlands','Denmark','Poland','Estonia',
'Portugal','Finland','Romania','France','Slovakia','Germany','Slovenia','Greece','Spain','Hungary','Sweden','Ireland']
df_out = df[df['location'].isin(EU_members)]
df_out.to_csv('data.csv')
Creates data.csv:

JSON from API call to pandas dataframe

I'm trying to get an API call and save it as a dataframe.
problem is that I need the data from the 'result' column.
Didn't succeed to do that.
I'm basically just trying to save the API call as a csv file in order to work with it.
P.S when I do this with a "JSON to CSV converter" from the web it does it as I wish. (example: https://konklone.io/json/)
import requests
import pandas as pd
import json
res = requests.get("http://api.etherscan.io/api?module=account&action=txlist&
address=0xddbd2b932c763ba5b1b7ae3b362eac3e8d40121a&startblock=0&
endblock=99999999&sort=asc&apikey=YourApiKeyToken")
j = res.json()
j
df = pd.DataFrame(j)
df.head()
output example picture

Try this
import requests
import pandas as pd
import json
res = requests.get("http://api.etherscan.io/api?module=account&action=txlist&address=0xddbd2b932c763ba5b1b7ae3b362eac3e8d40121a&startblock=0&endblock=99999999&sort=asc&apikey=YourApiKeyToken")
j = res.json()
# print(j)
filename ="temp.csv"
df = pd.DataFrame(j['result'])
print(df.head())
df.to_csv(filename)

Looks like you need.
df = pd.DataFrame(j["result"])

Convert a cell into different columns & rows of the DataFrame

I am trying to scrape a table out of a site. I have tried to convert data_row to a Pandas DataFrame; however, all the data are lumped in one cell of the DataFrame. Would you guys please help me convert the data_row into a Pandas DataFrame with "Business Mileage, "Charitable Mileage," "Medical mileage," and "Moving mileage" as rows and "2016," "2015," "2014," "2013," "2012," "2011," and "2010" as columns ?
from bs4 import BeautifulSoup
import urllib2
import pandas as pd
r = urllib2.urlopen('http://www.smbiz.com/sbrl003.html#cmv')
soup = BeautifulSoup(r)
print soup.prettify()
data_row = soup.findAll('pre')[0:1]