Using Pandas, I'm trying to extract value using the key but I keep failing to do so. Could you help me with this?
There's a csv file like below:
value
"{""id"":""1234"",""currency"":""USD""}"
"{""id"":""5678"",""currency"":""EUR""}"
I imported this file in Pandas and made a DataFrame out of it:
dataframe from a csv file
However, when I tried to extract the value using a key (e.g. df["id"]), I'm facing an error message.
I'd like to see a value 1234 or 5678 using df["id"]. Which step should I take to get it done? This may be a very basic question but I need your help. Thanks.
The csv file isn't being read in correctly.
You haven't set a delimiter; pandas can automatically detect a delimiter but hasn't done so in your case. See the read_csv documentation for more on this. Because the , the pandas dataframe has a single column, value, which has entire lines from your file as individual cells - the first entry is "{""id"":""1234"",""currency"":""USD""}". So, the file doesn't have a column id, and you can't select data by id.
The data aren't formatted as a pandas df, with row titles and columns of data. One option is to read in this data is to manually process each row, though there may be slicker options.
file = 'test.dat'
f = open(file,'r')
id_vals = []
currency = []
for line in f.readlines()[1:]:
## remove obfuscating characters
for c in '"{}\n':
line = line.replace(c,'')
line = line.split(',')
## extract values to two lists
id_vals.append(line[0][3:])
currency.append(line[1][9:])
You just need to clean up the CSV file a little and you are good. Here is every step:
# open your csv and read as a text string
with open('My_CSV.csv', 'r') as f:
my_csv_text = f.read()
# remove problematic strings
find_str = ['{', '}', '"', 'id:', 'currency:','value']
replace_str = ''
for i in find_str:
my_csv_text = re.sub(i, replace_str, my_csv_text)
# Create new csv file and save cleaned text
new_csv_path = './my_new_csv.csv' # or whatever path and name you want
with open(new_csv_path, 'w') as f:
f.write(my_csv_text)
# Create pandas dataframe
df = pd.read_csv('my_new_csv.csv', sep=',', names=['ID', 'Currency'])
print(df)
Output df:
ID Currency
0 1234 USD
1 5678 EUR
You need to extract each row of your dataframe using json.loads() or eval()
something like this:
import json
for row in df.iteritems():
print(json.loads(row.value)["id"])
# OR
print(eval(row.value)["id"])
I'm trying to read a csv file with pandas.
This file actually has only one row but it causes an error whenever I try to read it.
Something wrong seems happening in line 8 but I could hardly find the 8th line since there's clearly only one row on it.
I do like:
with codecs.open("path_to_file", "rU", "Shift-JIS", "ignore") as file:
df = pd.read_csv(file, header=None, sep="\t")
df
Then I get:
ParserError: Error tokenizing data. C error: Expected 1 fields in line 8, saw 3
I don't get what's really going on, so any of your advice will be appreciated.
I struggled with this almost a half day , I opened the csv with notepad and noticed that separate is TAB not comma and then tried belo combination.
df = pd.read_csv('C:\\myfile.csv',sep='\t', lineterminator='\r')
Try df = pd.read_csv(file, header=None, error_bad_lines=False)
The existing answer will not include these additional lines in your dataframe. If you'd like your dataframe to be as wide as its widest point, you can use the following:
delimiter = ','
max_columns = max(open(path_name, 'r'), key = lambda x: x.count(delimiter)).count(delimiter)
df = pd.read_csv(path_name, header = None, skiprows = 1, names = list(range(0,max_columns)))
Set skiprows = 1 if there's actually a header, you can always retrieve the header column names later.
You can also identify rows that have more columns populated than the number of column names in the original header.
I a importing a .csv file in python with pandas.
Here is the file format from the .csv :
a1;b1;c1;d1;e1;...
a2;b2;c2;d2;e2;...
.....
here is how get it :
from pandas import *
csv_path = "C:...."
data = read_csv(csv_path)
Now when I print the file I get that :
0 a1;b1;c1;d1;e1;...
1 a2;b2;c2;d2;e2;...
And so on... So I need help to read the file and split the values in columns, with the semi color character ;.
read_csv takes a sep param, in your case just pass sep=';' like so:
data = read_csv(csv_path, sep=';')
The reason it failed in your case is that the default value is ',' so it scrunched up all the columns as a single column entry.
In response to Morris' question above:
"Is there a way to programatically tell if a CSV is separated by , or ; ?"
This will tell you:
import pandas as pd
df_comma = pd.read_csv(your_csv_file_path, nrows=1,sep=",")
df_semi = pd.read_csv(your_csv_file_path, nrows=1, sep=";")
if df_comma.shape[1]>df_semi.shape[1]:
print("comma delimited")
else:
print("semicolon delimited")
I have a .csv to read into a DataFrame and the names of the columns are in the same .csv file in the previos rows. Usually I drop all the 'unnecesary' rows to create the DataFrame and then hardcode the names of each dataframe
Trigger time,2017-07-31,10:45:38
CH,Signal name,Input,Range,Filter,Span
CH1, "Tin_MIX_Air",TEMP,PT,Off,2000.000000,-200.000000,degC
CH2, "Tout_Fan2b",TEMP,PT,Off,2000.000000,-200.000000,degC
CH3, "Tout_Fan2a",TEMP,PT,Off,2000.000000,-200.000000,degC
CH4, "Tout_Fan1a",TEMP,PT,Off,2000.000000,-200.000000,degC
Here you can see the rows where the columns names are in double quotes "TinMix","Tout..",etc there are exactly 16 rows with names
Logic/Pulse,Off
Data
Number,Date&Time,ms,CH1,CH2,CH3,CH4,CH5,CH7,CH8,CH9,CH10,CH11,CH12,CH13,CH14,CH15,CH16,CH20,Alarm1-10,Alarm11-20,AlarmOut
NO.,Time,ms,degC,degC,degC,degC,degC,degC,%RH,%RH,degC,degC,degC,degC,degC,Pa,Pa,A,A1234567890,A1234567890,A1234
1,2017-07-31 10:45:38,000,+25.6,+26.2,+26.1,+26.0,+26.3,+25.7,+43.70,+37.22,+25.6,+25.3,+25.1,+25.3,+25.3,+0.25,+0.15,+0.00,LLLLLLLLLL,LLLLLLLLLL,LLLL
And here the values of each variables start.
What I need to do is create a Dataframe from this .csv and place these names in the columns names. I'm new to Python and I'm not very sure how to do it
import pandas as pd
path = r'path-to-file.csv'
data=pd.DataFrame()
with open(path, 'r') as f:
for line in f:
data = pd.concat([data, pd.DataFrame([tuple(line.strip().split(','))])], ignore_index=True)
data.drop(data.index[range(0,29)],inplace=True)
x=len(data.iloc[0])
data.drop(data.columns[[0,1,2,x-1,x-2,x-3]],axis=1,inplace=True)
data.reset_index(drop=True,inplace=True)
data = data.T.reset_index(drop=True).T
data = data.apply(pd.to_numeric)
This is what I've done so far to get my dataframe with the usefull data, I'm dropping all the other columns that arent useful to me and keeping only the values. Last three lines are to reset row/column indexes and to transform the whole df to floats. What I would like is to name the columns with each of the names I showed in the first piece of coding as a I said before I'm doing this manually as:
data.columns = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p']
But I would like to get them from the .csv file since theres a possibility on changing the CH# - "Name" combination
Thank you very much for the help!
Comment: possible for it to work within the other "OPEN " loop that I have?
Assume Column Names from Row 2 up to 6, Data from Row 7 up to EOF.
For instance (untested code)
data = None
columns = []
with open (path) as fh:
for row, line in enumerate (fh, 1):
if row > 2 and row <= 6:
ch, name = line.split(',')[:2]
columns.append(name)
else:
row_data = [tuple(line.strip().split(','))]
if not data:
data = pd.DataFrame(row_data, columns=columns, ignore_index=True)
else:
data.append(row_data)
Question: ... I would like to get them from the .csv file
Start with:
with open (path) as fh:
for row, line in enumerate (fh, 1):
if row > 2:
ch, name = line.split(',')[:2]
I'm trying to write the data from my list to just column 4
namelist = ['PEAR']
for name in namelist:
for man_year in yearlist:
for man_month in monthlist:
with open('{2}\{0}\{1}.csv'.format(man_year,man_month,name),'w') as filename:
writer = csv.writer(filename)
writer.writerow(name)
time.sleep(0.01)
it outputs to a csv like this
P E A R
4015854 234342 2442343 234242
How can I get it to go on just the 4th column?
PEAR
4015854 234342 2442343 234242
Replace the line writer.writerow(name) with,
writer.writerow(['', '', '', name])
When you pass the name to csvwriter it assumes the name as an iterable and write each character in a column.
So, for getting ride of this problem change the following line:
writer.writerow(name)
With:
writer.writerow([''] * (len(other_row)-1) + [name])
Here other_row can be one of the rest rows, but if you are sure about the length you can do something like:
writer.writerow([''] * (length-1) + [name])
Instead of writing '' to cells you don't want to touch, you could use df.at instead. For example, you could write df.at[index, ColumnName] = 10 which would change only the value of that specific cell.
You can read more about it here: Set value for particular cell in pandas DataFrame using index